public class SupervisedModelParametersSchema<P extends SupervisedModel.SupervisedParameters,S extends SupervisedModelParametersSchema<P,S>> extends ModelParametersSchema<P,S>
Schema.Meta| Modifier and Type | Field and Description |
|---|---|
boolean |
balance_classes
For imbalanced data, balance training data class counts via
over/under-sampling.
|
float[] |
class_sampling_factors
Desired over/under-sampling ratios per class (lexicographic order).
|
float |
max_after_balance_size
When classes are balanced, limit the resulting dataset size to the
specified multiple of the original dataset size.
|
int |
max_confusion_matrix_size
For classification models, the maximum size (in terms of classes) of
the confusion matrix for it to be printed.
|
int |
max_hit_ratio_k
The maximum number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)
|
static java.lang.String[] |
own_fields |
FrameV3.ColSpecifierV3 |
response_column |
ignore_const_cols, ignored_columns, model_id, score_each_iteration, training_frame, validation_frame__meta, _impl_class, _version_pattern| Constructor and Description |
|---|
SupervisedModelParametersSchema() |
append_field_arrays, fields, fillFromImpl, fillImpl, writeParametersJSONacceptsFrame, createAndFillImpl, createImpl, extractVersion, fillFromParms, getExperimentalVersion, getHighestSupportedVersion, getImplClass, getImplClass, getLatestVersion, getSchemaVersion, markdown, markdown, markdown, markdown, newInstance, register, registerAllSchemasIfNecessary, schema, schema, schema, schema, schema, schemaClass, schemaClass, schemaClass, schemaClass, schemasclone, frozenType, read_impl, read, readExternal, readJSON_impl, readJSON, toJsonString, write_impl, write, writeExternal, writeHTML_impl, writeHTML, writeJSON_impl, writeJSONpublic static java.lang.String[] own_fields
@API(help="Response column", is_member_of_frames={"training_frame","validation_frame"}, is_mutually_exclusive_with="ignored_columns", direction=INOUT) public FrameV3.ColSpecifierV3 response_column
@API(help="Balance training data class counts via over/under-sampling (for imbalanced data).", level=secondary, direction=INOUT) public boolean balance_classes
@API(help="Desired over/under-sampling ratios per class (in lexicographic order). If not specified, sampling factors will be automatically computed to obtain class balance during training. Requires balance_classes.", level=expert, direction=INOUT) public float[] class_sampling_factors
@API(help="Maximum relative size of the training data after balancing class counts (can be less than 1.0). Requires balance_classes.", level=expert, direction=INOUT) public float max_after_balance_size
@API(help="Maximum size (# classes) for confusion matrices to be printed in the Logs", level=secondary, direction=INOUT) public int max_confusion_matrix_size
@API(help="Max. number (top K) of predictions to use for hit ratio computation (for multi-class only, 0 to disable)", level=secondary, direction=INOUT) public int max_hit_ratio_k