hex.schemas

Class SparkSVMV3.SparkSVMParametersV3

java.lang.Object

water.Iced

water.api.Schema<I,S>

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

water.api.schemas3.ModelParametersSchemaV3<SparkSVMParameters,SparkSVMV3.SparkSVMParametersV3>

hex.schemas.SparkSVMV3.SparkSVMParametersV3

All Implemented Interfaces:

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

Enclosing class:

SparkSVMV3

public static final class SparkSVMV3.SparkSVMParametersV3
extends water.api.schemas3.ModelParametersSchemaV3<SparkSVMParameters,SparkSVMV3.SparkSVMParametersV3>

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	add_intercept
double	convergence_tol
static java.lang.String[]	fields
Gradient	gradient
water.api.schemas3.KeyV3.FrameKeyV3	initial_weights_frame
double	mini_batch_fraction
MissingValuesHandling	missing_values_handling
double	reg_param
double	step_size
double	threshold
Updater	updater

Fields inherited from class water.api.schemas3.ModelParametersSchemaV3

categorical_encoding, checkpoint, custom_distribution_func, custom_metric_func, distribution, export_checkpoints_dir, fold_assignment, fold_column, 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
SparkSVMParametersV3()

Method Summary

Modifier and Type	Method and Description
SparkSVMV3.SparkSVMParametersV3	fillFromImpl(SparkSVMParameters impl)
SparkSVMParameters	fillImpl(SparkSVMParameters impl)

Methods inherited from class water.api.schemas3.ModelParametersSchemaV3

append_field_arrays, extractDeclaredApiParameters, fields, 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, 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

fields

public static java.lang.String[] fields

initial_weights_frame

@API(help="Initial model weights.",
     direction=INOUT,
     gridable=true)
public water.api.schemas3.KeyV3.FrameKeyV3 initial_weights_frame

add_intercept

@API(help="Add intercept.",
     direction=INOUT,
     gridable=true,
     level=expert)
public boolean add_intercept

step_size

@API(help="Set step size",
     direction=INPUT,
     gridable=true,
     level=expert)
public double step_size

reg_param

@API(help="Set regularization parameter",
     direction=INPUT,
     gridable=true,
     level=expert)
public double reg_param

convergence_tol

@API(help="Set convergence tolerance",
     direction=INPUT,
     gridable=true,
     level=expert)
public double convergence_tol

mini_batch_fraction

@API(help="Set mini batch fraction",
     direction=INPUT,
     gridable=true,
     level=expert)
public double mini_batch_fraction

threshold

@API(help="Set threshold that separates positive predictions from negative ones. NaN for raw prediction.",
     direction=INOUT,
     gridable=true,
     level=expert)
public double threshold

updater

@API(help="Set the updater for SGD.",
     direction=INPUT,
     values={"L2","L1","Simple"},
     required=true,
     gridable=true,
     level=expert)
public Updater updater

gradient

@API(help="Set the gradient computation type for SGD.",
     direction=INPUT,
     values={"Hinge","LeastSquares","Logistic"},
     required=true,
     gridable=true,
     level=expert)
public Gradient gradient

missing_values_handling

@API(level=expert,
     direction=INOUT,
     gridable=true,
     values={"NotAllowed","Skip","MeanImputation"},
     help="Handling of missing values. Either NotAllowed, Skip or MeanImputation.")
public MissingValuesHandling missing_values_handling

Constructor Detail

SparkSVMParametersV3

public SparkSVMParametersV3()

Method Detail

fillFromImpl

public SparkSVMV3.SparkSVMParametersV3 fillFromImpl(SparkSVMParameters impl)

Overrides:

fillFromImpl in class water.api.schemas3.ModelParametersSchemaV3<SparkSVMParameters,SparkSVMV3.SparkSVMParametersV3>

fillImpl

public SparkSVMParameters fillImpl(SparkSVMParameters impl)

Overrides:

fillImpl in class water.api.schemas3.ModelParametersSchemaV3<SparkSVMParameters,SparkSVMV3.SparkSVMParametersV3>