public class AggregatorParametersV99 extends ModelParametersSchema
| Modifier and Type | Field and Description |
|---|---|
int |
k
Rank of matrix approximation
|
int |
max_iterations
Maximum number of iterations for PCA
|
PcaPCAModelPCAParametersMethod |
pca_method
Method for computing PCA (Caution: Power and GLRM are currently experimental and unstable)
|
double |
radius_scale
Radius scaling
|
long |
seed
RNG seed for initialization
|
DataInfoTransformType |
transform
Transformation of training data
|
boolean |
use_all_factor_levels
Whether first factor level is included in each categorical expansion
|
checkpoint, fold_assignment, fold_column, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_predictions, max_runtime_secs, model_id, nfolds, offset_column, parallelize_cross_validation, response_column, score_each_iteration, stopping_metric, stopping_rounds, stopping_tolerance, training_frame, validation_frame, weights_column| Constructor and Description |
|---|
AggregatorParametersV99() |
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
toString()
Return the contents of this object as a JSON String.
|
public double radius_scale
public DataInfoTransformType transform
public PcaPCAModelPCAParametersMethod pca_method
public int k
public int max_iterations
public long seed
public boolean use_all_factor_levels
public java.lang.String toString()
toString in class ModelParametersSchema