hex.schemas

Class TargetEncoderV3.TargetEncoderParametersV3

java.lang.Object

water.Iced

water.api.Schema<I,S>

water.api.schemas3.SchemaV3<P,S>

water.api.schemas3.ModelParametersSchemaV3<TargetEncoderModel.TargetEncoderParameters,TargetEncoderV3.TargetEncoderParametersV3>

hex.schemas.TargetEncoderV3.TargetEncoderParametersV3

All Implemented Interfaces:

java.io.Externalizable, java.io.Serializable, java.lang.Cloneable, water.Freezable

Enclosing class:

TargetEncoderV3

public static class TargetEncoderV3.TargetEncoderParametersV3
extends water.api.schemas3.ModelParametersSchemaV3<TargetEncoderModel.TargetEncoderParameters,TargetEncoderV3.TargetEncoderParametersV3>

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class water.api.schemas3.SchemaV3

water.api.schemas3.SchemaV3.Meta

Nested classes/interfaces inherited from class water.api.Schema

water.api.Schema.AutoParseable

Field Summary

Fields

Modifier and Type	Field and Description
boolean	blending
java.lang.String[][]	columns_to_encode
TargetEncoderModel.DataLeakageHandlingStrategy	data_leakage_handling
double	inflection_point
boolean	keep_original_categorical_columns
double	noise
long	seed
double	smoothing

Fields inherited from class water.api.schemas3.ModelParametersSchemaV3

auc_type, categorical_encoding, checkpoint, custom_distribution_func, custom_metric_func, distribution, export_checkpoints_dir, fold_assignment, fold_column, gainslift_bins, huber_alpha, ignore_const_cols, ignored_columns, keep_cross_validation_fold_assignment, keep_cross_validation_models, keep_cross_validation_predictions, max_categorical_levels, max_runtime_secs, model_id, nfolds, offset_column, parallelize_cross_validation, quantile_alpha, response_column, score_each_iteration, stopping_metric, stopping_rounds, stopping_tolerance, training_frame, tweedie_power, validation_frame, weights_column

Fields inherited from class water.api.schemas3.SchemaV3

__meta

Constructor Summary

Constructors

Constructor and Description
TargetEncoderParametersV3()

Method Summary

Modifier and Type	Method and Description
java.lang.String[]	fields()

Methods inherited from class water.api.schemas3.ModelParametersSchemaV3

append_field_arrays, extractDeclaredApiParameters, fillFromImpl, fillImpl, getAdditionalParameters, writeParametersJSON

Methods inherited from class water.api.schemas3.SchemaV3

writeJSON

Methods inherited from class water.api.Schema

createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromAny, fillFromBody, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillFromParms, fillImpl, getImplClass, getImplClass, getSchemaName, getSchemaType, getSchemaVersion, init_meta, markdown, markdown, newInstance, newInstance, setField, setSchemaType_doNotCall

Methods inherited from class water.Iced

asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonString, write, writeExternal

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

columns_to_encode

@API(help="List of categorical columns or groups of categorical columns to encode. When groups of columns are specified, each group is encoded as a single column (interactions are created internally).",
     level=critical)
public java.lang.String[][] columns_to_encode

keep_original_categorical_columns

@API(help="If true, the original non-encoded categorical features will remain in the result frame.",
     level=critical)
public boolean keep_original_categorical_columns

blending

@API(help="If true, enables blending of posterior probabilities (computed for a given categorical value) with prior probabilities (computed on the entire set). This allows to mitigate the effect of categorical values with small cardinality. The blending effect can be tuned using the `inflection_point` and `smoothing` parameters.",
     level=secondary)
public boolean blending

inflection_point

@API(help="Inflection point of the sigmoid used to blend probabilities (see `blending` parameter). For a given categorical value, if it appears less that `inflection_point` in a data sample, then the influence of the posterior probability will be smaller than the prior.",
     level=secondary)
public double inflection_point

smoothing

@API(help="Smoothing factor corresponds to the inverse of the slope at the inflection point on the sigmoid used to blend probabilities (see `blending` parameter). If smoothing tends towards 0, then the sigmoid used for blending turns into a Heaviside step function.",
     level=secondary)
public double smoothing

data_leakage_handling

@API(help="Data leakage handling strategy used to generate the encoding. Supported options are:\n1) \"none\" (default) - no holdout, using the entire training frame.\n2) \"leave_one_out\" - current row\'s response value is subtracted from the per-level frequencies pre-calculated on the entire training frame.\n3) \"k_fold\" - encodings for a fold are generated based on out-of-fold data.\n",
     valuesProvider=TargetEncoderV3.DataLeakageHandlingStrategyProvider.class,
     level=secondary)
public TargetEncoderModel.DataLeakageHandlingStrategy data_leakage_handling

noise

@API(help="The amount of noise to add to the encoded column. Use 0 to disable noise, and -1 (=AUTO) to let the algorithm determine a reasonable amount of noise.",
     direction=INPUT,
     gridable=true,
     level=expert)
public double noise

seed

@API(help="Seed used to generate the noise. By default, the seed is chosen randomly.",
     direction=INPUT,
     level=expert)
public long seed

Constructor Detail

TargetEncoderParametersV3

public TargetEncoderParametersV3()

Method Detail

fields

public java.lang.String[] fields()

Overrides:

fields in class water.api.schemas3.ModelParametersSchemaV3<TargetEncoderModel.TargetEncoderParameters,TargetEncoderV3.TargetEncoderParametersV3>