hex.kmeans

Class KMeans

java.lang.Object

water.Iced

hex.ModelBuilder<M,P,O>

hex.ClusteringModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

hex.kmeans.KMeans

All Implemented Interfaces:

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

public class KMeans
extends hex.ClusteringModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

Scalable K-Means++ (KMeans||)
http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
http://www.youtube.com/watch?v=cigXAxV3XcY

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	KMeans.Initialization
static class	KMeans.IterationTask

Nested classes/interfaces inherited from class hex.ModelBuilder

hex.ModelBuilder.BuilderVisibility, hex.ModelBuilder.Driver, hex.ModelBuilder.FilterCols, hex.ModelBuilder.ModelTrainingCoordinator, hex.ModelBuilder.ValidationMessage

Field Summary

Fields inherited from class hex.ModelBuilder

_coordinator, _desc, _eventPublisher, _fold, _input_parms, _job, _messages, _nclass, _offset, _orig_projection_array, _origDomains, _origNames, _origTrain, _parms, _priorClassDist, _removedCols, _response, _result, _startUpOnceModelBuilder, _train, _treatment, _valid, _vresponse, _weights

Constructor Summary

Constructors

Constructor and Description
KMeans(boolean startup_once)
KMeans(KMeansModel.KMeansParameters parms)
KMeans(KMeansModel.KMeansParameters parms, water.Job job)

Method Summary

Modifier and Type	Method and Description
hex.ModelCategory[]	can_build()
protected void	checkMemoryFootPrint_impl()
void	cv_makeAggregateModelMetrics(hex.ModelMetrics.MetricBuilder[] mbs)
hex.ToEigenVec	getToEigenVec()
boolean	haveMojo()
boolean	havePojo()
void	init(boolean expensive) Initialize the ModelBuilder, validating all arguments and preparing the training frame.
protected hex.kmeans.KMeans.KMeansDriver	trainModelImpl() Start the KMeans training Job on an F/J thread.

Methods inherited from class hex.ClusteringModelBuilder

isSupervised

Methods inherited from class hex.ModelBuilder

algoName, algos, builderVisibility, canLearnFromNAs, checkCustomMetricForEarlyStopping, checkDistributions, checkEarlyStoppingReproducibility, checkMemoryFootPrint, checkResponseVariable, clearInitState, clearValidationErrors, computeCrossValidation, computePriorClassDistribution, cv_buildModels, cv_canBuildMainModelInParallel, cv_computeAndSetOptimalParameters, cv_initStoppingParameters, cv_mainModelScores, cv_scoreCVModels, cv_updateOptimalParameters, defaultKey, desiredChunks, dest, error_count, error, get, getMessagesByFieldAndSeverity, getName, getSysProperty, hasFoldCol, hasOffsetCol, hasTreatmentCol, hasWeightCol, hide, ignoreBadColumns, ignoreConstColumns, ignoreInvalidColumns, ignoreStringColumns, ignoreUuidColumns, info, init_adaptFrameToTrain, init_getNClass, initWorkspace, isClassifier, isResponseOptional, isStopped, javaName, logMe, make, make, make, makeCVMetrics, makeCVModelBuilder, makeParameters, makePojoWriter, message, nclasses, nFoldCV, nFoldWork, nModelsInParallel, nModelsInParallel, nModelsInParallel, numSpecialCols, paramName, raiseReproducibilityWarning, rebalance, remainingTimeSecs, response, schemaDirectory, separateFeatureVecs, setMaxRuntimeSecsForMainModel, setTrain, setValid, shouldReorder, smallDataSize, stop_requested, timeout, train, trainModel, trainModel, trainModelNested, trainModelNested, trainModelOnH2ONode, valid, validateBinaryResponse, validateStoppingMetric, validationErrors, validationWarnings, vresponse, warn

Methods inherited from class water.Iced

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

Methods inherited from class java.lang.Object

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

Constructor Detail

KMeans

public KMeans(KMeansModel.KMeansParameters parms)

KMeans

public KMeans(KMeansModel.KMeansParameters parms,
              water.Job job)

KMeans

public KMeans(boolean startup_once)

Method Detail

getToEigenVec

public hex.ToEigenVec getToEigenVec()

Overrides:

getToEigenVec in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

can_build

public hex.ModelCategory[] can_build()

Specified by:

can_build in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

havePojo

public boolean havePojo()

Overrides:

havePojo in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

haveMojo

public boolean haveMojo()

Overrides:

haveMojo in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

trainModelImpl

protected hex.kmeans.KMeans.KMeansDriver trainModelImpl()

Start the KMeans training Job on an F/J thread.

Specified by:

trainModelImpl in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

checkMemoryFootPrint_impl

protected void checkMemoryFootPrint_impl()

Overrides:

checkMemoryFootPrint_impl in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

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();". Validate K, max_iterations and the number of rows.

Overrides:

init in class hex.ClusteringModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>

cv_makeAggregateModelMetrics

public void cv_makeAggregateModelMetrics(hex.ModelMetrics.MetricBuilder[] mbs)

Overrides:

cv_makeAggregateModelMetrics in class hex.ModelBuilder<KMeansModel,KMeansModel.KMeansParameters,KMeansModel.KMeansOutput>