public class ANOVAGLM extends hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
Modifier and Type | Field and Description |
---|---|
int |
_numberOfModels |
int |
_numberOfPredCombo |
int |
_numberOfPredictors |
int[] |
_predictorColumnStart |
java.lang.String[][] |
_transformedColNames |
_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 and Description |
---|
ANOVAGLM(ANOVAGLMModel.ANOVAGLMParameters parms) |
ANOVAGLM(ANOVAGLMModel.ANOVAGLMParameters parms,
water.Key<ANOVAGLMModel> key) |
ANOVAGLM(boolean startup_once) |
Modifier and Type | Method and Description |
---|---|
hex.ModelCategory[] |
can_build() |
boolean |
haveMojo() |
boolean |
havePojo() |
void |
init(boolean expensive) |
boolean |
isSupervised() |
protected int |
nModelsInParallel(int folds) |
protected hex.anovaglm.ANOVAGLM.ANOVAGLMDriver |
trainModelImpl() |
algoName, algos, builderVisibility, canLearnFromNAs, checkCustomMetricForEarlyStopping, checkDistributions, checkEarlyStoppingReproducibility, checkMemoryFootPrint_impl, checkMemoryFootPrint, checkResponseVariable, clearInitState, clearValidationErrors, computeCrossValidation, computePriorClassDistribution, cv_buildModels, cv_canBuildMainModelInParallel, cv_computeAndSetOptimalParameters, cv_initStoppingParameters, cv_mainModelScores, cv_makeAggregateModelMetrics, cv_scoreCVModels, cv_updateOptimalParameters, defaultKey, desiredChunks, dest, error_count, error, get, getMessagesByFieldAndSeverity, getName, getSysProperty, getToEigenVec, 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, 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
public int _numberOfModels
public int _numberOfPredCombo
public int _numberOfPredictors
public java.lang.String[][] _transformedColNames
public int[] _predictorColumnStart
public ANOVAGLM(boolean startup_once)
public ANOVAGLM(ANOVAGLMModel.ANOVAGLMParameters parms)
public ANOVAGLM(ANOVAGLMModel.ANOVAGLMParameters parms, water.Key<ANOVAGLMModel> key)
protected int nModelsInParallel(int folds)
nModelsInParallel
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
protected hex.anovaglm.ANOVAGLM.ANOVAGLMDriver trainModelImpl()
trainModelImpl
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
public hex.ModelCategory[] can_build()
can_build
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
public boolean isSupervised()
isSupervised
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
public boolean haveMojo()
haveMojo
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
public boolean havePojo()
havePojo
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>
public void init(boolean expensive)
init
in class hex.ModelBuilder<ANOVAGLMModel,ANOVAGLMModel.ANOVAGLMParameters,ANOVAGLMModel.ANOVAGLMModelOutput>