hex.quantile

Class Quantile

java.lang.Object

water.Iced

hex.ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

hex.quantile.Quantile

All Implemented Interfaces:

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

public class Quantile
extends ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

Quantile model builder... building a simple QuantileModel

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Quantile.StratifiedQuantilesTask

Nested classes/interfaces inherited from class hex.ModelBuilder

ModelBuilder.BuilderVisibility, ModelBuilder.Driver, ModelBuilder.ValidationMessage

Field Summary

Fields inherited from class hex.ModelBuilder

_fold, _job, _messages, _nclass, _offset, _parms, _removedCols, _response, _result, _train, _valid, _vresponse, _weights

Constructor Summary

Constructors

Constructor and Description
Quantile(QuantileModel.QuantileParameters parms)

Method Summary

Methods

Modifier and Type	Method and Description
hex.ModelCategory[]	can_build() List containing the categories of models that this builder can build.
protected int	desiredChunks(Frame original_fr, boolean local) Find desired number of chunks.
void	init(boolean expensive) Initialize the ModelBuilder, validating all arguments and preparing the training frame.
protected boolean	logMe()
long	progressUnits()
ModelBuilder.Driver	trainModelImpl() Model-specific implementation of model training

Methods inherited from class hex.ModelBuilder

algoName, algos, builderVisibility, checkDistributions, checkMemoryFootPrint, clearInitState, clearValidationErrors, computeCrossValidation, computePriorClassDistribution, cv_AssignFold, cv_mainModelScores, cv_makeFramesAndBuilders, cv_makeWeights, cv_runCVBuilds, cv_scoreCVModels, defaultKey, dest, error_count, error, get, hasFoldCol, hasOffsetCol, hasWeightCol, hide, ignoreBadColumns, ignoreConstColumns, ignoreStringColumns, info, isClassifier, isStopped, isSupervised, javaName, make, message, modifyParmsForCrossValidationMainModel, nclasses, nFoldCV, numSpecialCols, paramName, rebalance, response, separateFeatureVecs, train, trainModel, trainModelNested, valid, validationErrors, vresponse, warn

Methods inherited from class water.Iced

clone, copyOver, frozenType, read_impl, read, readExternal, readJSON_impl, readJSON, toJsonString, write_impl, write, writeExternal, writeJSON_impl, writeJSON

Methods inherited from class java.lang.Object

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

Constructor Detail

Quantile

public Quantile(QuantileModel.QuantileParameters parms)

Method Detail

logMe

protected boolean logMe()

Overrides:

logMe in class ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

trainModelImpl

public ModelBuilder.Driver trainModelImpl()

Description copied from class: ModelBuilder

Model-specific implementation of model training

Specified by:

trainModelImpl in class ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

Returns:

A F/J Job, which, when executed, does the build. F/J is NOT started.

progressUnits

public long progressUnits()

Specified by:

progressUnits in class ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

can_build

public hex.ModelCategory[] can_build()

Description copied from class: ModelBuilder

List containing the categories of models that this builder can build. Each ModelBuilder must have one of these.

Specified by:

can_build in class ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

desiredChunks

protected int desiredChunks(Frame original_fr,
                boolean local)

Description copied from class: ModelBuilder

Find desired number of chunks. If fewer, dataset will be rebalanced.

Overrides:

desiredChunks in class ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>

Returns:

Lower bound on number of chunks after rebalancing.

init

public void init(boolean expensive)

Initialize the ModelBuilder, validating all arguments and preparing the training frame. This call is expected to be overridden in the subclasses and each subclass will start with "super.init();". This call is made by the front-end whenever the GUI is clicked, and needs to be fast; heavy-weight prep needs to wait for the trainModel() call. Validate the probs.

Overrides:

init in class ModelBuilder<QuantileModel,QuantileModel.QuantileParameters,QuantileModel.QuantileOutput>