public interface Predictions
| Modifier and Type | Method and Description |
|---|---|
retrofit2.Call<ModelMetricsListSchemaV3> |
predict(java.lang.String model,
java.lang.String frame) |
retrofit2.Call<ModelMetricsListSchemaV3> |
predict(java.lang.String model,
java.lang.String frame,
java.lang.String predictions_frame,
java.lang.String deviances_frame,
boolean reconstruction_error,
boolean reconstruction_error_per_feature,
int deep_features_hidden_layer,
java.lang.String deep_features_hidden_layer_name,
boolean reconstruct_train,
boolean project_archetypes,
boolean reverse_transform,
boolean leaf_node_assignment,
int exemplar_index,
boolean deviances,
java.lang.String custom_metric_func,
java.lang.String _exclude_fields)
Score (generate predictions) for the specified Frame with the specified Model.
|
retrofit2.Call<JobV3> |
predictAsync(java.lang.String model,
java.lang.String frame) |
retrofit2.Call<JobV3> |
predictAsync(java.lang.String model,
java.lang.String frame,
java.lang.String predictions_frame,
java.lang.String deviances_frame,
boolean reconstruction_error,
boolean reconstruction_error_per_feature,
int deep_features_hidden_layer,
java.lang.String deep_features_hidden_layer_name,
boolean reconstruct_train,
boolean project_archetypes,
boolean reverse_transform,
boolean leaf_node_assignment,
int exemplar_index,
boolean deviances,
java.lang.String custom_metric_func,
java.lang.String _exclude_fields)
Score (generate predictions) for the specified Frame with the specified Model.
|
@FormUrlEncoded
@POST(value="/3/Predictions/models/{model}/frames/{frame}")
retrofit2.Call<ModelMetricsListSchemaV3> predict(@Path(value="model")
java.lang.String model,
@Path(value="frame")
java.lang.String frame,
@Field(value="predictions_frame")
java.lang.String predictions_frame,
@Field(value="deviances_frame")
java.lang.String deviances_frame,
@Field(value="reconstruction_error")
boolean reconstruction_error,
@Field(value="reconstruction_error_per_feature")
boolean reconstruction_error_per_feature,
@Field(value="deep_features_hidden_layer")
int deep_features_hidden_layer,
@Field(value="deep_features_hidden_layer_name")
java.lang.String deep_features_hidden_layer_name,
@Field(value="reconstruct_train")
boolean reconstruct_train,
@Field(value="project_archetypes")
boolean project_archetypes,
@Field(value="reverse_transform")
boolean reverse_transform,
@Field(value="leaf_node_assignment")
boolean leaf_node_assignment,
@Field(value="exemplar_index")
int exemplar_index,
@Field(value="deviances")
boolean deviances,
@Field(value="custom_metric_func")
java.lang.String custom_metric_func,
@Field(value="_exclude_fields")
java.lang.String _exclude_fields)
model - Key of Model of interest (optional)frame - Key of Frame of interest (optional)predictions_frame - Key of predictions frame, if predictions are requested (optional)deviances_frame - Key for the frame containing per-observation deviances (optional)reconstruction_error - Compute reconstruction error (optional, only for Deep Learning AutoEncoder models)reconstruction_error_per_feature - Compute reconstruction error per feature (optional, only for Deep
Learning AutoEncoder models)deep_features_hidden_layer - Extract Deep Features for given hidden layer (optional, only for Deep Learning
models)deep_features_hidden_layer_name - Extract Deep Features for given hidden layer by name (optional, only for
Deep Water models)reconstruct_train - Reconstruct original training frame (optional, only for GLRM models)project_archetypes - Project GLRM archetypes back into original feature space (optional, only for GLRM
models)reverse_transform - Reverse transformation applied during training to model output (optional, only for GLRM
models)leaf_node_assignment - Return the leaf node assignment (optional, only for DRF/GBM models)exemplar_index - Retrieve all members for a given exemplar (optional, only for Aggregator models)deviances - Compute the deviances per row (optional, only for classification or regression models)custom_metric_func - Reference to custom evaluation function, format: `language:keyName=funcName`_exclude_fields - Comma-separated list of JSON field paths to exclude from the result, used like:
"/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"@FormUrlEncoded
@POST(value="/3/Predictions/models/{model}/frames/{frame}")
retrofit2.Call<ModelMetricsListSchemaV3> predict(@Path(value="model")
java.lang.String model,
@Path(value="frame")
java.lang.String frame)
@FormUrlEncoded
@POST(value="/4/Predictions/models/{model}/frames/{frame}")
retrofit2.Call<JobV3> predictAsync(@Path(value="model")
java.lang.String model,
@Path(value="frame")
java.lang.String frame,
@Field(value="predictions_frame")
java.lang.String predictions_frame,
@Field(value="deviances_frame")
java.lang.String deviances_frame,
@Field(value="reconstruction_error")
boolean reconstruction_error,
@Field(value="reconstruction_error_per_feature")
boolean reconstruction_error_per_feature,
@Field(value="deep_features_hidden_layer")
int deep_features_hidden_layer,
@Field(value="deep_features_hidden_layer_name")
java.lang.String deep_features_hidden_layer_name,
@Field(value="reconstruct_train")
boolean reconstruct_train,
@Field(value="project_archetypes")
boolean project_archetypes,
@Field(value="reverse_transform")
boolean reverse_transform,
@Field(value="leaf_node_assignment")
boolean leaf_node_assignment,
@Field(value="exemplar_index")
int exemplar_index,
@Field(value="deviances")
boolean deviances,
@Field(value="custom_metric_func")
java.lang.String custom_metric_func,
@Field(value="_exclude_fields")
java.lang.String _exclude_fields)
model - Key of Model of interest (optional)frame - Key of Frame of interest (optional)predictions_frame - Key of predictions frame, if predictions are requested (optional)deviances_frame - Key for the frame containing per-observation deviances (optional)reconstruction_error - Compute reconstruction error (optional, only for Deep Learning AutoEncoder models)reconstruction_error_per_feature - Compute reconstruction error per feature (optional, only for Deep
Learning AutoEncoder models)deep_features_hidden_layer - Extract Deep Features for given hidden layer (optional, only for Deep Learning
models)deep_features_hidden_layer_name - Extract Deep Features for given hidden layer by name (optional, only for
Deep Water models)reconstruct_train - Reconstruct original training frame (optional, only for GLRM models)project_archetypes - Project GLRM archetypes back into original feature space (optional, only for GLRM
models)reverse_transform - Reverse transformation applied during training to model output (optional, only for GLRM
models)leaf_node_assignment - Return the leaf node assignment (optional, only for DRF/GBM models)exemplar_index - Retrieve all members for a given exemplar (optional, only for Aggregator models)deviances - Compute the deviances per row (optional, only for classification or regression models)custom_metric_func - Reference to custom evaluation function, format: `language:keyName=funcName`_exclude_fields - Comma-separated list of JSON field paths to exclude from the result, used like:
"/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"@FormUrlEncoded
@POST(value="/4/Predictions/models/{model}/frames/{frame}")
retrofit2.Call<JobV3> predictAsync(@Path(value="model")
java.lang.String model,
@Path(value="frame")
java.lang.String frame)