hex.schemas

Class PCAV3.PCAParametersV3

java.lang.Object

water.Iced

water.api.Schema<I,S>

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

water.api.schemas3.ModelParametersSchemaV3<PCAModel.PCAParameters,PCAV3.PCAParametersV3>

hex.schemas.PCAV3.PCAParametersV3

All Implemented Interfaces:

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

Enclosing class:

PCAV3

public static final class PCAV3.PCAParametersV3
extends water.api.schemas3.ModelParametersSchemaV3<PCAModel.PCAParameters,PCAV3.PCAParametersV3>

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	compute_metrics
static java.lang.String[]	fields
boolean	impute_missing
int	k
int	max_iterations
PCAImplementation	pca_impl
PCAModel.PCAParameters.Method	pca_method
long	seed
DataInfo.TransformType	transform
boolean	use_all_factor_levels

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
PCAParametersV3()

Method Summary

Methods inherited from class water.api.schemas3.ModelParametersSchemaV3

append_field_arrays, extractDeclaredApiParameters, fields, 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, toJsonBytes, 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

transform

@API(help="Transformation of training data",
     values={"NONE","STANDARDIZE","NORMALIZE","DEMEAN","DESCALE"},
     gridable=true)
public DataInfo.TransformType transform

pca_method

@API(help="Specify the algorithm to use for computing the principal components: GramSVD - uses a distributed computation of the Gram matrix, followed by a local SVD; Power - computes the SVD using the power iteration method (experimental); Randomized - uses randomized subspace iteration method; GLRM - fits a generalized low-rank model with L2 loss function and no regularization and solves for the SVD using local matrix algebra (experimental)",
     values={"GramSVD","Power","Randomized","GLRM"})
public PCAModel.PCAParameters.Method pca_method

pca_impl

@API(help="Specify the implementation to use for computing PCA (via SVD or EVD): MTJ_EVD_DENSEMATRIX - eigenvalue decompositions for dense matrix using MTJ; MTJ_EVD_SYMMMATRIX - eigenvalue decompositions for symmetric matrix using MTJ; MTJ_SVD_DENSEMATRIX - singular-value decompositions for dense matrix using MTJ; JAMA - eigenvalue decompositions for dense matrix using JAMA. References: JAMA - http://math.nist.gov/javanumerics/jama/; MTJ - https://github.com/fommil/matrix-toolkits-java/",
     values={"MTJ_EVD_DENSEMATRIX","MTJ_EVD_SYMMMATRIX","MTJ_SVD_DENSEMATRIX","JAMA"})
public PCAImplementation pca_impl

k

@API(help="Rank of matrix approximation",
     required=true,
     direction=INOUT,
     gridable=true)
public int k

max_iterations

@API(help="Maximum training iterations",
     direction=INOUT,
     gridable=true)
public int max_iterations

seed

@API(help="RNG seed for initialization",
     direction=INOUT)
public long seed

use_all_factor_levels

@API(help="Whether first factor level is included in each categorical expansion",
     direction=INOUT)
public boolean use_all_factor_levels

compute_metrics

@API(help="Whether to compute metrics on the training data",
     direction=INOUT)
public boolean compute_metrics

impute_missing

@API(help="Whether to impute missing entries with the column mean",
     direction=INOUT)
public boolean impute_missing

Constructor Detail

PCAParametersV3

public PCAParametersV3()