public class DeepLearning extends hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
| Modifier and Type | Class and Description |
|---|---|
class |
DeepLearning.DeepLearningDriver |
| Constructor and Description |
|---|
DeepLearning(boolean startup_once) |
DeepLearning(DeepLearningModel.DeepLearningParameters parms)
Main constructor from Deep Learning parameters
|
DeepLearning(DeepLearningModel.DeepLearningParameters parms,
water.Key<DeepLearningModel> key) |
| Modifier and Type | Method and Description |
|---|---|
hex.ModelCategory[] |
can_build()
Types of models we can build with DeepLearning
|
protected void |
checkMemoryFootPrint_impl() |
void |
cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders) |
protected int |
desiredChunks(water.fvec.Frame original_fr,
boolean local) |
hex.ToEigenVec |
getToEigenVec() |
boolean |
haveMojo() |
boolean |
havePojo() |
void |
init(boolean expensive)
Initialize the ModelBuilder, validating all arguments and preparing the
training frame.
|
boolean |
isSupervised() |
protected water.fvec.Frame |
rebalance(water.fvec.Frame original_fr,
boolean local,
java.lang.String name) |
protected DeepLearning.DeepLearningDriver |
trainModelImpl() |
algoName, algos, builderVisibility, bulkBuildModels, canLearnFromNAs, checkDistributions, checkMemoryFootPrint, checkResponseVariable, clearInitState, clearValidationErrors, computeCrossValidation, computePriorClassDistribution, cv_AssignFold, cv_buildModels, cv_mainModelScores, cv_makeWeights, cv_scoreCVModels, defaultKey, dest, error_count, error, get, getName, getSysProperty, hasFoldCol, hasOffsetCol, hasWeightCol, hide, ignoreBadColumns, ignoreConstColumns, ignoreInvalidColumns, ignoreStringColumns, ignoreUuidColumns, info, init_adaptFrameToTrain, init_getNClass, initWorkspace, isClassifier, isResponseOptional, isStopped, javaName, logMe, make, make, make, message, nclasses, nFoldCV, nFoldWork, nModelsInParallel, nModelsInParallel, nModelsInParallel, numSpecialCols, paramName, response, schemaDirectory, separateFeatureVecs, setModelBuilderListener, setTrain, shouldReorder, specialColNames, stop_requested, timeout, train, trainModel, trainModelNested, trainModelNested, trainModelOnH2ONode, valid, validateStoppingMetric, validationErrors, vresponse, warnpublic DeepLearning(DeepLearningModel.DeepLearningParameters parms)
public DeepLearning(DeepLearningModel.DeepLearningParameters parms, water.Key<DeepLearningModel> key)
public DeepLearning(boolean startup_once)
public hex.ModelCategory[] can_build()
can_build in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public boolean havePojo()
havePojo in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public boolean haveMojo()
haveMojo in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public hex.ToEigenVec getToEigenVec()
getToEigenVec in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public boolean isSupervised()
isSupervised in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>protected DeepLearning.DeepLearningDriver trainModelImpl()
trainModelImpl in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public void init(boolean expensive)
init in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>protected void checkMemoryFootPrint_impl()
checkMemoryFootPrint_impl in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public void cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders)
cv_computeAndSetOptimalParameters in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>protected water.fvec.Frame rebalance(water.fvec.Frame original_fr,
boolean local,
java.lang.String name)
rebalance in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>protected int desiredChunks(water.fvec.Frame original_fr,
boolean local)
desiredChunks in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>