public interface ModelBuilders
| Modifier and Type | Interface and Description |
|---|---|
static class |
ModelBuilders.Helper |
| Modifier and Type | Method and Description |
|---|---|
retrofit2.Call<ModelIdV3> |
calcModelId(java.lang.String algo,
java.lang.String _exclude_fields)
Return a new unique model_id for the specified algorithm.
|
retrofit2.Call<ModelBuildersV3> |
fetch(java.lang.String algo)
Return the Model Builder metadata for the specified algorithm.
|
retrofit2.Call<ModelBuildersV3> |
list()
Return the Model Builder metadata for all available algorithms.
|
retrofit2.Call<AggregatorV99> |
train_aggregator(double radius_scale,
DataInfoTransformType transform,
PcaPCAModelPCAParametersMethod pca_method,
int k,
int max_iterations,
long seed,
boolean use_all_factor_levels,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a Aggregator model.
|
retrofit2.Call<DeepLearningV3> |
train_deeplearning(boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
boolean overwrite_with_best_model,
boolean autoencoder,
boolean use_all_factor_levels,
boolean standardize,
DeeplearningDeepLearningModelDeepLearningParametersActivation activation,
int[] hidden,
double epochs,
long train_samples_per_iteration,
double target_ratio_comm_to_comp,
long seed,
boolean adaptive_rate,
double rho,
double epsilon,
double rate,
double rate_annealing,
double rate_decay,
double momentum_start,
double momentum_ramp,
double momentum_stable,
boolean nesterov_accelerated_gradient,
double input_dropout_ratio,
double[] hidden_dropout_ratios,
double l1,
double l2,
float max_w2,
DeeplearningDeepLearningModelDeepLearningParametersInitialWeightDistribution initial_weight_distribution,
double initial_weight_scale,
java.lang.String[] initial_weights,
java.lang.String[] initial_biases,
DeeplearningDeepLearningModelDeepLearningParametersLoss loss,
DistributionFamily distribution,
double tweedie_power,
double quantile_alpha,
double score_interval,
long score_training_samples,
long score_validation_samples,
double score_duty_cycle,
double classification_stop,
double regression_stop,
boolean quiet_mode,
DeeplearningDeepLearningModelDeepLearningParametersClassSamplingMethod score_validation_sampling,
boolean diagnostics,
boolean variable_importances,
boolean fast_mode,
boolean force_load_balance,
boolean replicate_training_data,
boolean single_node_mode,
boolean shuffle_training_data,
DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling,
boolean sparse,
boolean col_major,
double average_activation,
double sparsity_beta,
int max_categorical_features,
boolean reproducible,
boolean export_weights_and_biases,
int mini_batch_size,
boolean elastic_averaging,
double elastic_averaging_moving_rate,
double elastic_averaging_regularization,
java.lang.String pretrained_autoencoder,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a DeepLearning model.
|
retrofit2.Call<DRFV3> |
train_drf(int mtries,
boolean binomial_double_trees,
boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
int ntrees,
int max_depth,
double min_rows,
int nbins,
int nbins_top_level,
int nbins_cats,
double r2_stopping,
long seed,
boolean build_tree_one_node,
double sample_rate,
double[] sample_rate_per_class,
double col_sample_rate_per_tree,
double col_sample_rate_change_per_level,
int score_tree_interval,
double min_split_improvement,
TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a DRF model.
|
retrofit2.Call<GBMV3> |
train_gbm(double learn_rate,
double learn_rate_annealing,
DistributionFamily distribution,
double quantile_alpha,
double tweedie_power,
double col_sample_rate,
double max_abs_leafnode_pred,
boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
int ntrees,
int max_depth,
double min_rows,
int nbins,
int nbins_top_level,
int nbins_cats,
double r2_stopping,
long seed,
boolean build_tree_one_node,
double sample_rate,
double[] sample_rate_per_class,
double col_sample_rate_per_tree,
double col_sample_rate_change_per_level,
int score_tree_interval,
double min_split_improvement,
TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a GBM model.
|
retrofit2.Call<GLMV3> |
train_glm(GlmGLMModelGLMParametersFamily family,
double tweedie_variance_power,
double tweedie_link_power,
GlmGLMModelGLMParametersSolver solver,
double[] alpha,
double[] lambda,
boolean lambda_search,
int nlambdas,
boolean standardize,
DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling,
boolean non_negative,
int max_iterations,
double beta_epsilon,
double objective_epsilon,
double gradient_epsilon,
double obj_reg,
GlmGLMModelGLMParametersLink link,
boolean intercept,
double prior,
double lambda_min_ratio,
java.lang.String beta_constraints,
int max_active_predictors,
java.lang.String[] interactions,
boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
boolean compute_p_values,
boolean remove_collinear_columns,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a GLM model.
|
retrofit2.Call<GLRMV3> |
train_glrm(DataInfoTransformType transform,
int k,
GlrmGLRMModelGLRMParametersLoss loss,
GlrmGLRMModelGLRMParametersLoss multi_loss,
GlrmGLRMModelGLRMParametersLoss[] loss_by_col,
int[] loss_by_col_idx,
int period,
GlrmGLRMModelGLRMParametersRegularizer regularization_x,
GlrmGLRMModelGLRMParametersRegularizer regularization_y,
double gamma_x,
double gamma_y,
int max_iterations,
int max_updates,
double init_step_size,
double min_step_size,
long seed,
GlrmGLRMInitialization init,
SvdSVDModelSVDParametersMethod svd_method,
java.lang.String user_y,
java.lang.String user_x,
java.lang.String loading_name,
boolean expand_user_y,
boolean impute_original,
boolean recover_svd,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a GLRM model.
|
retrofit2.Call<KMeansV3> |
train_kmeans(java.lang.String user_points,
int max_iterations,
boolean standardize,
long seed,
KmeansKMeansInitialization init,
int k,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a KMeans model.
|
retrofit2.Call<NaiveBayesV3> |
train_naivebayes(boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
double laplace,
double min_sdev,
double eps_sdev,
double min_prob,
double eps_prob,
boolean compute_metrics,
long seed,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a NaiveBayes model.
|
retrofit2.Call<PCAV3> |
train_pca(DataInfoTransformType transform,
PcaPCAModelPCAParametersMethod pca_method,
int k,
int max_iterations,
long seed,
boolean use_all_factor_levels,
boolean compute_metrics,
boolean impute_missing,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a PCA model.
|
retrofit2.Call<SVDV99> |
train_svd(DataInfoTransformType transform,
SvdSVDModelSVDParametersMethod svd_method,
int nv,
int max_iterations,
long seed,
boolean keep_u,
java.lang.String u_name,
boolean use_all_factor_levels,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Train a SVD model.
|
retrofit2.Call<AggregatorV99> |
validate_parameters_aggregator(double radius_scale,
DataInfoTransformType transform,
PcaPCAModelPCAParametersMethod pca_method,
int k,
int max_iterations,
long seed,
boolean use_all_factor_levels,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of Aggregator model builder parameters.
|
retrofit2.Call<DeepLearningV3> |
validate_parameters_deeplearning(boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
boolean overwrite_with_best_model,
boolean autoencoder,
boolean use_all_factor_levels,
boolean standardize,
DeeplearningDeepLearningModelDeepLearningParametersActivation activation,
int[] hidden,
double epochs,
long train_samples_per_iteration,
double target_ratio_comm_to_comp,
long seed,
boolean adaptive_rate,
double rho,
double epsilon,
double rate,
double rate_annealing,
double rate_decay,
double momentum_start,
double momentum_ramp,
double momentum_stable,
boolean nesterov_accelerated_gradient,
double input_dropout_ratio,
double[] hidden_dropout_ratios,
double l1,
double l2,
float max_w2,
DeeplearningDeepLearningModelDeepLearningParametersInitialWeightDistribution initial_weight_distribution,
double initial_weight_scale,
java.lang.String[] initial_weights,
java.lang.String[] initial_biases,
DeeplearningDeepLearningModelDeepLearningParametersLoss loss,
DistributionFamily distribution,
double tweedie_power,
double quantile_alpha,
double score_interval,
long score_training_samples,
long score_validation_samples,
double score_duty_cycle,
double classification_stop,
double regression_stop,
boolean quiet_mode,
DeeplearningDeepLearningModelDeepLearningParametersClassSamplingMethod score_validation_sampling,
boolean diagnostics,
boolean variable_importances,
boolean fast_mode,
boolean force_load_balance,
boolean replicate_training_data,
boolean single_node_mode,
boolean shuffle_training_data,
DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling,
boolean sparse,
boolean col_major,
double average_activation,
double sparsity_beta,
int max_categorical_features,
boolean reproducible,
boolean export_weights_and_biases,
int mini_batch_size,
boolean elastic_averaging,
double elastic_averaging_moving_rate,
double elastic_averaging_regularization,
java.lang.String pretrained_autoencoder,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of DeepLearning model builder parameters.
|
retrofit2.Call<DRFV3> |
validate_parameters_drf(int mtries,
boolean binomial_double_trees,
boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
int ntrees,
int max_depth,
double min_rows,
int nbins,
int nbins_top_level,
int nbins_cats,
double r2_stopping,
long seed,
boolean build_tree_one_node,
double sample_rate,
double[] sample_rate_per_class,
double col_sample_rate_per_tree,
double col_sample_rate_change_per_level,
int score_tree_interval,
double min_split_improvement,
TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of DRF model builder parameters.
|
retrofit2.Call<GBMV3> |
validate_parameters_gbm(double learn_rate,
double learn_rate_annealing,
DistributionFamily distribution,
double quantile_alpha,
double tweedie_power,
double col_sample_rate,
double max_abs_leafnode_pred,
boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
int ntrees,
int max_depth,
double min_rows,
int nbins,
int nbins_top_level,
int nbins_cats,
double r2_stopping,
long seed,
boolean build_tree_one_node,
double sample_rate,
double[] sample_rate_per_class,
double col_sample_rate_per_tree,
double col_sample_rate_change_per_level,
int score_tree_interval,
double min_split_improvement,
TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of GBM model builder parameters.
|
retrofit2.Call<GLMV3> |
validate_parameters_glm(GlmGLMModelGLMParametersFamily family,
double tweedie_variance_power,
double tweedie_link_power,
GlmGLMModelGLMParametersSolver solver,
double[] alpha,
double[] lambda,
boolean lambda_search,
int nlambdas,
boolean standardize,
DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling,
boolean non_negative,
int max_iterations,
double beta_epsilon,
double objective_epsilon,
double gradient_epsilon,
double obj_reg,
GlmGLMModelGLMParametersLink link,
boolean intercept,
double prior,
double lambda_min_ratio,
java.lang.String beta_constraints,
int max_active_predictors,
java.lang.String[] interactions,
boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
boolean compute_p_values,
boolean remove_collinear_columns,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of GLM model builder parameters.
|
retrofit2.Call<GLRMV3> |
validate_parameters_glrm(DataInfoTransformType transform,
int k,
GlrmGLRMModelGLRMParametersLoss loss,
GlrmGLRMModelGLRMParametersLoss multi_loss,
GlrmGLRMModelGLRMParametersLoss[] loss_by_col,
int[] loss_by_col_idx,
int period,
GlrmGLRMModelGLRMParametersRegularizer regularization_x,
GlrmGLRMModelGLRMParametersRegularizer regularization_y,
double gamma_x,
double gamma_y,
int max_iterations,
int max_updates,
double init_step_size,
double min_step_size,
long seed,
GlrmGLRMInitialization init,
SvdSVDModelSVDParametersMethod svd_method,
java.lang.String user_y,
java.lang.String user_x,
java.lang.String loading_name,
boolean expand_user_y,
boolean impute_original,
boolean recover_svd,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of GLRM model builder parameters.
|
retrofit2.Call<KMeansV3> |
validate_parameters_kmeans(java.lang.String user_points,
int max_iterations,
boolean standardize,
long seed,
KmeansKMeansInitialization init,
int k,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of KMeans model builder parameters.
|
retrofit2.Call<NaiveBayesV3> |
validate_parameters_naivebayes(boolean balance_classes,
float[] class_sampling_factors,
float max_after_balance_size,
int max_confusion_matrix_size,
int max_hit_ratio_k,
double laplace,
double min_sdev,
double eps_sdev,
double min_prob,
double eps_prob,
boolean compute_metrics,
long seed,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of NaiveBayes model builder parameters.
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retrofit2.Call<PCAV3> |
validate_parameters_pca(DataInfoTransformType transform,
PcaPCAModelPCAParametersMethod pca_method,
int k,
int max_iterations,
long seed,
boolean use_all_factor_levels,
boolean compute_metrics,
boolean impute_missing,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of PCA model builder parameters.
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retrofit2.Call<SVDV99> |
validate_parameters_svd(DataInfoTransformType transform,
SvdSVDModelSVDParametersMethod svd_method,
int nv,
int max_iterations,
long seed,
boolean keep_u,
java.lang.String u_name,
boolean use_all_factor_levels,
java.lang.String model_id,
java.lang.String training_frame,
java.lang.String validation_frame,
int nfolds,
boolean keep_cross_validation_predictions,
boolean keep_cross_validation_fold_assignment,
boolean parallelize_cross_validation,
java.lang.String response_column,
java.lang.String weights_column,
java.lang.String offset_column,
java.lang.String fold_column,
ModelParametersFoldAssignmentScheme fold_assignment,
java.lang.String[] ignored_columns,
boolean ignore_const_cols,
boolean score_each_iteration,
java.lang.String checkpoint,
int stopping_rounds,
double max_runtime_secs,
ScoreKeeperStoppingMetric stopping_metric,
double stopping_tolerance)
Validate a set of SVD model builder parameters.
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@FormUrlEncoded
@POST(value="/3/ModelBuilders/{algo}/model_id")
retrofit2.Call<ModelIdV3> calcModelId(@Path(value="algo")
java.lang.String algo,
@Field(value="_exclude_fields")
java.lang.String _exclude_fields)
@GET(value="/3/ModelBuilders/{algo}")
retrofit2.Call<ModelBuildersV3> fetch(@Path(value="algo")
java.lang.String algo)
@GET(value="/3/ModelBuilders") retrofit2.Call<ModelBuildersV3> list()
@FormUrlEncoded @POST(value="/3/ModelBuilders/deeplearning") retrofit2.Call<DeepLearningV3> train_deeplearning(@Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="overwrite_with_best_model") boolean overwrite_with_best_model, @Field(value="autoencoder") boolean autoencoder, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="standardize") boolean standardize, @Field(value="activation") DeeplearningDeepLearningModelDeepLearningParametersActivation activation, @Field(value="hidden") int[] hidden, @Field(value="epochs") double epochs, @Field(value="train_samples_per_iteration") long train_samples_per_iteration, @Field(value="target_ratio_comm_to_comp") double target_ratio_comm_to_comp, @Field(value="seed") long seed, @Field(value="adaptive_rate") boolean adaptive_rate, @Field(value="rho") double rho, @Field(value="epsilon") double epsilon, @Field(value="rate") double rate, @Field(value="rate_annealing") double rate_annealing, @Field(value="rate_decay") double rate_decay, @Field(value="momentum_start") double momentum_start, @Field(value="momentum_ramp") double momentum_ramp, @Field(value="momentum_stable") double momentum_stable, @Field(value="nesterov_accelerated_gradient") boolean nesterov_accelerated_gradient, @Field(value="input_dropout_ratio") double input_dropout_ratio, @Field(value="hidden_dropout_ratios") double[] hidden_dropout_ratios, @Field(value="l1") double l1, @Field(value="l2") double l2, @Field(value="max_w2") float max_w2, @Field(value="initial_weight_distribution") DeeplearningDeepLearningModelDeepLearningParametersInitialWeightDistribution initial_weight_distribution, @Field(value="initial_weight_scale") double initial_weight_scale, @Field(value="initial_weights") java.lang.String[] initial_weights, @Field(value="initial_biases") java.lang.String[] initial_biases, @Field(value="loss") DeeplearningDeepLearningModelDeepLearningParametersLoss loss, @Field(value="distribution") DistributionFamily distribution, @Field(value="tweedie_power") double tweedie_power, @Field(value="quantile_alpha") double quantile_alpha, @Field(value="score_interval") double score_interval, @Field(value="score_training_samples") long score_training_samples, @Field(value="score_validation_samples") long score_validation_samples, @Field(value="score_duty_cycle") double score_duty_cycle, @Field(value="classification_stop") double classification_stop, @Field(value="regression_stop") double regression_stop, @Field(value="quiet_mode") boolean quiet_mode, @Field(value="score_validation_sampling") DeeplearningDeepLearningModelDeepLearningParametersClassSamplingMethod score_validation_sampling, @Field(value="diagnostics") boolean diagnostics, @Field(value="variable_importances") boolean variable_importances, @Field(value="fast_mode") boolean fast_mode, @Field(value="force_load_balance") boolean force_load_balance, @Field(value="replicate_training_data") boolean replicate_training_data, @Field(value="single_node_mode") boolean single_node_mode, @Field(value="shuffle_training_data") boolean shuffle_training_data, @Field(value="missing_values_handling") DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling, @Field(value="sparse") boolean sparse, @Field(value="col_major") boolean col_major, @Field(value="average_activation") double average_activation, @Field(value="sparsity_beta") double sparsity_beta, @Field(value="max_categorical_features") int max_categorical_features, @Field(value="reproducible") boolean reproducible, @Field(value="export_weights_and_biases") boolean export_weights_and_biases, @Field(value="mini_batch_size") int mini_batch_size, @Field(value="elastic_averaging") boolean elastic_averaging, @Field(value="elastic_averaging_moving_rate") double elastic_averaging_moving_rate, @Field(value="elastic_averaging_regularization") double elastic_averaging_regularization, @Field(value="pretrained_autoencoder") java.lang.String pretrained_autoencoder, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/deeplearning/parameters") retrofit2.Call<DeepLearningV3> validate_parameters_deeplearning(@Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="overwrite_with_best_model") boolean overwrite_with_best_model, @Field(value="autoencoder") boolean autoencoder, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="standardize") boolean standardize, @Field(value="activation") DeeplearningDeepLearningModelDeepLearningParametersActivation activation, @Field(value="hidden") int[] hidden, @Field(value="epochs") double epochs, @Field(value="train_samples_per_iteration") long train_samples_per_iteration, @Field(value="target_ratio_comm_to_comp") double target_ratio_comm_to_comp, @Field(value="seed") long seed, @Field(value="adaptive_rate") boolean adaptive_rate, @Field(value="rho") double rho, @Field(value="epsilon") double epsilon, @Field(value="rate") double rate, @Field(value="rate_annealing") double rate_annealing, @Field(value="rate_decay") double rate_decay, @Field(value="momentum_start") double momentum_start, @Field(value="momentum_ramp") double momentum_ramp, @Field(value="momentum_stable") double momentum_stable, @Field(value="nesterov_accelerated_gradient") boolean nesterov_accelerated_gradient, @Field(value="input_dropout_ratio") double input_dropout_ratio, @Field(value="hidden_dropout_ratios") double[] hidden_dropout_ratios, @Field(value="l1") double l1, @Field(value="l2") double l2, @Field(value="max_w2") float max_w2, @Field(value="initial_weight_distribution") DeeplearningDeepLearningModelDeepLearningParametersInitialWeightDistribution initial_weight_distribution, @Field(value="initial_weight_scale") double initial_weight_scale, @Field(value="initial_weights") java.lang.String[] initial_weights, @Field(value="initial_biases") java.lang.String[] initial_biases, @Field(value="loss") DeeplearningDeepLearningModelDeepLearningParametersLoss loss, @Field(value="distribution") DistributionFamily distribution, @Field(value="tweedie_power") double tweedie_power, @Field(value="quantile_alpha") double quantile_alpha, @Field(value="score_interval") double score_interval, @Field(value="score_training_samples") long score_training_samples, @Field(value="score_validation_samples") long score_validation_samples, @Field(value="score_duty_cycle") double score_duty_cycle, @Field(value="classification_stop") double classification_stop, @Field(value="regression_stop") double regression_stop, @Field(value="quiet_mode") boolean quiet_mode, @Field(value="score_validation_sampling") DeeplearningDeepLearningModelDeepLearningParametersClassSamplingMethod score_validation_sampling, @Field(value="diagnostics") boolean diagnostics, @Field(value="variable_importances") boolean variable_importances, @Field(value="fast_mode") boolean fast_mode, @Field(value="force_load_balance") boolean force_load_balance, @Field(value="replicate_training_data") boolean replicate_training_data, @Field(value="single_node_mode") boolean single_node_mode, @Field(value="shuffle_training_data") boolean shuffle_training_data, @Field(value="missing_values_handling") DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling, @Field(value="sparse") boolean sparse, @Field(value="col_major") boolean col_major, @Field(value="average_activation") double average_activation, @Field(value="sparsity_beta") double sparsity_beta, @Field(value="max_categorical_features") int max_categorical_features, @Field(value="reproducible") boolean reproducible, @Field(value="export_weights_and_biases") boolean export_weights_and_biases, @Field(value="mini_batch_size") int mini_batch_size, @Field(value="elastic_averaging") boolean elastic_averaging, @Field(value="elastic_averaging_moving_rate") double elastic_averaging_moving_rate, @Field(value="elastic_averaging_regularization") double elastic_averaging_regularization, @Field(value="pretrained_autoencoder") java.lang.String pretrained_autoencoder, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/glm") retrofit2.Call<GLMV3> train_glm(@Field(value="family") GlmGLMModelGLMParametersFamily family, @Field(value="tweedie_variance_power") double tweedie_variance_power, @Field(value="tweedie_link_power") double tweedie_link_power, @Field(value="solver") GlmGLMModelGLMParametersSolver solver, @Field(value="alpha") double[] alpha, @Field(value="lambda") double[] lambda, @Field(value="lambda_search") boolean lambda_search, @Field(value="nlambdas") int nlambdas, @Field(value="standardize") boolean standardize, @Field(value="missing_values_handling") DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling, @Field(value="non_negative") boolean non_negative, @Field(value="max_iterations") int max_iterations, @Field(value="beta_epsilon") double beta_epsilon, @Field(value="objective_epsilon") double objective_epsilon, @Field(value="gradient_epsilon") double gradient_epsilon, @Field(value="obj_reg") double obj_reg, @Field(value="link") GlmGLMModelGLMParametersLink link, @Field(value="intercept") boolean intercept, @Field(value="prior") double prior, @Field(value="lambda_min_ratio") double lambda_min_ratio, @Field(value="beta_constraints") java.lang.String beta_constraints, @Field(value="max_active_predictors") int max_active_predictors, @Field(value="interactions") java.lang.String[] interactions, @Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="compute_p_values") boolean compute_p_values, @Field(value="remove_collinear_columns") boolean remove_collinear_columns, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/glm/parameters") retrofit2.Call<GLMV3> validate_parameters_glm(@Field(value="family") GlmGLMModelGLMParametersFamily family, @Field(value="tweedie_variance_power") double tweedie_variance_power, @Field(value="tweedie_link_power") double tweedie_link_power, @Field(value="solver") GlmGLMModelGLMParametersSolver solver, @Field(value="alpha") double[] alpha, @Field(value="lambda") double[] lambda, @Field(value="lambda_search") boolean lambda_search, @Field(value="nlambdas") int nlambdas, @Field(value="standardize") boolean standardize, @Field(value="missing_values_handling") DeeplearningDeepLearningModelDeepLearningParametersMissingValuesHandling missing_values_handling, @Field(value="non_negative") boolean non_negative, @Field(value="max_iterations") int max_iterations, @Field(value="beta_epsilon") double beta_epsilon, @Field(value="objective_epsilon") double objective_epsilon, @Field(value="gradient_epsilon") double gradient_epsilon, @Field(value="obj_reg") double obj_reg, @Field(value="link") GlmGLMModelGLMParametersLink link, @Field(value="intercept") boolean intercept, @Field(value="prior") double prior, @Field(value="lambda_min_ratio") double lambda_min_ratio, @Field(value="beta_constraints") java.lang.String beta_constraints, @Field(value="max_active_predictors") int max_active_predictors, @Field(value="interactions") java.lang.String[] interactions, @Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="compute_p_values") boolean compute_p_values, @Field(value="remove_collinear_columns") boolean remove_collinear_columns, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/glrm") retrofit2.Call<GLRMV3> train_glrm(@Field(value="transform") DataInfoTransformType transform, @Field(value="k") int k, @Field(value="loss") GlrmGLRMModelGLRMParametersLoss loss, @Field(value="multi_loss") GlrmGLRMModelGLRMParametersLoss multi_loss, @Field(value="loss_by_col") GlrmGLRMModelGLRMParametersLoss[] loss_by_col, @Field(value="loss_by_col_idx") int[] loss_by_col_idx, @Field(value="period") int period, @Field(value="regularization_x") GlrmGLRMModelGLRMParametersRegularizer regularization_x, @Field(value="regularization_y") GlrmGLRMModelGLRMParametersRegularizer regularization_y, @Field(value="gamma_x") double gamma_x, @Field(value="gamma_y") double gamma_y, @Field(value="max_iterations") int max_iterations, @Field(value="max_updates") int max_updates, @Field(value="init_step_size") double init_step_size, @Field(value="min_step_size") double min_step_size, @Field(value="seed") long seed, @Field(value="init") GlrmGLRMInitialization init, @Field(value="svd_method") SvdSVDModelSVDParametersMethod svd_method, @Field(value="user_y") java.lang.String user_y, @Field(value="user_x") java.lang.String user_x, @Field(value="loading_name") java.lang.String loading_name, @Field(value="expand_user_y") boolean expand_user_y, @Field(value="impute_original") boolean impute_original, @Field(value="recover_svd") boolean recover_svd, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/glrm/parameters") retrofit2.Call<GLRMV3> validate_parameters_glrm(@Field(value="transform") DataInfoTransformType transform, @Field(value="k") int k, @Field(value="loss") GlrmGLRMModelGLRMParametersLoss loss, @Field(value="multi_loss") GlrmGLRMModelGLRMParametersLoss multi_loss, @Field(value="loss_by_col") GlrmGLRMModelGLRMParametersLoss[] loss_by_col, @Field(value="loss_by_col_idx") int[] loss_by_col_idx, @Field(value="period") int period, @Field(value="regularization_x") GlrmGLRMModelGLRMParametersRegularizer regularization_x, @Field(value="regularization_y") GlrmGLRMModelGLRMParametersRegularizer regularization_y, @Field(value="gamma_x") double gamma_x, @Field(value="gamma_y") double gamma_y, @Field(value="max_iterations") int max_iterations, @Field(value="max_updates") int max_updates, @Field(value="init_step_size") double init_step_size, @Field(value="min_step_size") double min_step_size, @Field(value="seed") long seed, @Field(value="init") GlrmGLRMInitialization init, @Field(value="svd_method") SvdSVDModelSVDParametersMethod svd_method, @Field(value="user_y") java.lang.String user_y, @Field(value="user_x") java.lang.String user_x, @Field(value="loading_name") java.lang.String loading_name, @Field(value="expand_user_y") boolean expand_user_y, @Field(value="impute_original") boolean impute_original, @Field(value="recover_svd") boolean recover_svd, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/kmeans") retrofit2.Call<KMeansV3> train_kmeans(@Field(value="user_points") java.lang.String user_points, @Field(value="max_iterations") int max_iterations, @Field(value="standardize") boolean standardize, @Field(value="seed") long seed, @Field(value="init") KmeansKMeansInitialization init, @Field(value="k") int k, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/kmeans/parameters") retrofit2.Call<KMeansV3> validate_parameters_kmeans(@Field(value="user_points") java.lang.String user_points, @Field(value="max_iterations") int max_iterations, @Field(value="standardize") boolean standardize, @Field(value="seed") long seed, @Field(value="init") KmeansKMeansInitialization init, @Field(value="k") int k, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/naivebayes") retrofit2.Call<NaiveBayesV3> train_naivebayes(@Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="laplace") double laplace, @Field(value="min_sdev") double min_sdev, @Field(value="eps_sdev") double eps_sdev, @Field(value="min_prob") double min_prob, @Field(value="eps_prob") double eps_prob, @Field(value="compute_metrics") boolean compute_metrics, @Field(value="seed") long seed, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/naivebayes/parameters") retrofit2.Call<NaiveBayesV3> validate_parameters_naivebayes(@Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="laplace") double laplace, @Field(value="min_sdev") double min_sdev, @Field(value="eps_sdev") double eps_sdev, @Field(value="min_prob") double min_prob, @Field(value="eps_prob") double eps_prob, @Field(value="compute_metrics") boolean compute_metrics, @Field(value="seed") long seed, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/pca") retrofit2.Call<PCAV3> train_pca(@Field(value="transform") DataInfoTransformType transform, @Field(value="pca_method") PcaPCAModelPCAParametersMethod pca_method, @Field(value="k") int k, @Field(value="max_iterations") int max_iterations, @Field(value="seed") long seed, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="compute_metrics") boolean compute_metrics, @Field(value="impute_missing") boolean impute_missing, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/pca/parameters") retrofit2.Call<PCAV3> validate_parameters_pca(@Field(value="transform") DataInfoTransformType transform, @Field(value="pca_method") PcaPCAModelPCAParametersMethod pca_method, @Field(value="k") int k, @Field(value="max_iterations") int max_iterations, @Field(value="seed") long seed, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="compute_metrics") boolean compute_metrics, @Field(value="impute_missing") boolean impute_missing, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/99/ModelBuilders/svd") retrofit2.Call<SVDV99> train_svd(@Field(value="transform") DataInfoTransformType transform, @Field(value="svd_method") SvdSVDModelSVDParametersMethod svd_method, @Field(value="nv") int nv, @Field(value="max_iterations") int max_iterations, @Field(value="seed") long seed, @Field(value="keep_u") boolean keep_u, @Field(value="u_name") java.lang.String u_name, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/99/ModelBuilders/svd/parameters") retrofit2.Call<SVDV99> validate_parameters_svd(@Field(value="transform") DataInfoTransformType transform, @Field(value="svd_method") SvdSVDModelSVDParametersMethod svd_method, @Field(value="nv") int nv, @Field(value="max_iterations") int max_iterations, @Field(value="seed") long seed, @Field(value="keep_u") boolean keep_u, @Field(value="u_name") java.lang.String u_name, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/drf") retrofit2.Call<DRFV3> train_drf(@Field(value="mtries") int mtries, @Field(value="binomial_double_trees") boolean binomial_double_trees, @Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="ntrees") int ntrees, @Field(value="max_depth") int max_depth, @Field(value="min_rows") double min_rows, @Field(value="nbins") int nbins, @Field(value="nbins_top_level") int nbins_top_level, @Field(value="nbins_cats") int nbins_cats, @Field(value="r2_stopping") double r2_stopping, @Field(value="seed") long seed, @Field(value="build_tree_one_node") boolean build_tree_one_node, @Field(value="sample_rate") double sample_rate, @Field(value="sample_rate_per_class") double[] sample_rate_per_class, @Field(value="col_sample_rate_per_tree") double col_sample_rate_per_tree, @Field(value="col_sample_rate_change_per_level") double col_sample_rate_change_per_level, @Field(value="score_tree_interval") int score_tree_interval, @Field(value="min_split_improvement") double min_split_improvement, @Field(value="histogram_type") TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/drf/parameters") retrofit2.Call<DRFV3> validate_parameters_drf(@Field(value="mtries") int mtries, @Field(value="binomial_double_trees") boolean binomial_double_trees, @Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="ntrees") int ntrees, @Field(value="max_depth") int max_depth, @Field(value="min_rows") double min_rows, @Field(value="nbins") int nbins, @Field(value="nbins_top_level") int nbins_top_level, @Field(value="nbins_cats") int nbins_cats, @Field(value="r2_stopping") double r2_stopping, @Field(value="seed") long seed, @Field(value="build_tree_one_node") boolean build_tree_one_node, @Field(value="sample_rate") double sample_rate, @Field(value="sample_rate_per_class") double[] sample_rate_per_class, @Field(value="col_sample_rate_per_tree") double col_sample_rate_per_tree, @Field(value="col_sample_rate_change_per_level") double col_sample_rate_change_per_level, @Field(value="score_tree_interval") int score_tree_interval, @Field(value="min_split_improvement") double min_split_improvement, @Field(value="histogram_type") TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/gbm") retrofit2.Call<GBMV3> train_gbm(@Field(value="learn_rate") double learn_rate, @Field(value="learn_rate_annealing") double learn_rate_annealing, @Field(value="distribution") DistributionFamily distribution, @Field(value="quantile_alpha") double quantile_alpha, @Field(value="tweedie_power") double tweedie_power, @Field(value="col_sample_rate") double col_sample_rate, @Field(value="max_abs_leafnode_pred") double max_abs_leafnode_pred, @Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="ntrees") int ntrees, @Field(value="max_depth") int max_depth, @Field(value="min_rows") double min_rows, @Field(value="nbins") int nbins, @Field(value="nbins_top_level") int nbins_top_level, @Field(value="nbins_cats") int nbins_cats, @Field(value="r2_stopping") double r2_stopping, @Field(value="seed") long seed, @Field(value="build_tree_one_node") boolean build_tree_one_node, @Field(value="sample_rate") double sample_rate, @Field(value="sample_rate_per_class") double[] sample_rate_per_class, @Field(value="col_sample_rate_per_tree") double col_sample_rate_per_tree, @Field(value="col_sample_rate_change_per_level") double col_sample_rate_change_per_level, @Field(value="score_tree_interval") int score_tree_interval, @Field(value="min_split_improvement") double min_split_improvement, @Field(value="histogram_type") TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/3/ModelBuilders/gbm/parameters") retrofit2.Call<GBMV3> validate_parameters_gbm(@Field(value="learn_rate") double learn_rate, @Field(value="learn_rate_annealing") double learn_rate_annealing, @Field(value="distribution") DistributionFamily distribution, @Field(value="quantile_alpha") double quantile_alpha, @Field(value="tweedie_power") double tweedie_power, @Field(value="col_sample_rate") double col_sample_rate, @Field(value="max_abs_leafnode_pred") double max_abs_leafnode_pred, @Field(value="balance_classes") boolean balance_classes, @Field(value="class_sampling_factors") float[] class_sampling_factors, @Field(value="max_after_balance_size") float max_after_balance_size, @Field(value="max_confusion_matrix_size") int max_confusion_matrix_size, @Field(value="max_hit_ratio_k") int max_hit_ratio_k, @Field(value="ntrees") int ntrees, @Field(value="max_depth") int max_depth, @Field(value="min_rows") double min_rows, @Field(value="nbins") int nbins, @Field(value="nbins_top_level") int nbins_top_level, @Field(value="nbins_cats") int nbins_cats, @Field(value="r2_stopping") double r2_stopping, @Field(value="seed") long seed, @Field(value="build_tree_one_node") boolean build_tree_one_node, @Field(value="sample_rate") double sample_rate, @Field(value="sample_rate_per_class") double[] sample_rate_per_class, @Field(value="col_sample_rate_per_tree") double col_sample_rate_per_tree, @Field(value="col_sample_rate_change_per_level") double col_sample_rate_change_per_level, @Field(value="score_tree_interval") int score_tree_interval, @Field(value="min_split_improvement") double min_split_improvement, @Field(value="histogram_type") TreeSharedTreeModelSharedTreeParametersHistogramType histogram_type, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/99/ModelBuilders/aggregator") retrofit2.Call<AggregatorV99> train_aggregator(@Field(value="radius_scale") double radius_scale, @Field(value="transform") DataInfoTransformType transform, @Field(value="pca_method") PcaPCAModelPCAParametersMethod pca_method, @Field(value="k") int k, @Field(value="max_iterations") int max_iterations, @Field(value="seed") long seed, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)
@FormUrlEncoded @POST(value="/99/ModelBuilders/aggregator/parameters") retrofit2.Call<AggregatorV99> validate_parameters_aggregator(@Field(value="radius_scale") double radius_scale, @Field(value="transform") DataInfoTransformType transform, @Field(value="pca_method") PcaPCAModelPCAParametersMethod pca_method, @Field(value="k") int k, @Field(value="max_iterations") int max_iterations, @Field(value="seed") long seed, @Field(value="use_all_factor_levels") boolean use_all_factor_levels, @Field(value="model_id") java.lang.String model_id, @Field(value="training_frame") java.lang.String training_frame, @Field(value="validation_frame") java.lang.String validation_frame, @Field(value="nfolds") int nfolds, @Field(value="keep_cross_validation_predictions") boolean keep_cross_validation_predictions, @Field(value="keep_cross_validation_fold_assignment") boolean keep_cross_validation_fold_assignment, @Field(value="parallelize_cross_validation") boolean parallelize_cross_validation, @Field(value="response_column") java.lang.String response_column, @Field(value="weights_column") java.lang.String weights_column, @Field(value="offset_column") java.lang.String offset_column, @Field(value="fold_column") java.lang.String fold_column, @Field(value="fold_assignment") ModelParametersFoldAssignmentScheme fold_assignment, @Field(value="ignored_columns") java.lang.String[] ignored_columns, @Field(value="ignore_const_cols") boolean ignore_const_cols, @Field(value="score_each_iteration") boolean score_each_iteration, @Field(value="checkpoint") java.lang.String checkpoint, @Field(value="stopping_rounds") int stopping_rounds, @Field(value="max_runtime_secs") double max_runtime_secs, @Field(value="stopping_metric") ScoreKeeperStoppingMetric stopping_metric, @Field(value="stopping_tolerance") double stopping_tolerance)