def __init__(self,
standardize=True,
family="gaussian",
link="family_default",
solver="AUTO",
tweedieVariancePower=0.0,
tweedieLinkPower=0.0,
alphaValue=None,
lambdaValue=None,
missingValuesHandling="MeanImputation",
prior=-1.0,
lambdaSearch=False,
nlambdas=-1,
nonNegative=False,
exactLambdas=False,
lambdaMinRatio=-1.0,
maxIterations=-1,
intercept=True,
betaEpsilon=1e-4,
objectiveEpsilon=-1.0,
gradientEpsilon=-1.0,
objReg=-1.0,
computePValues=False,
removeCollinearCols=False,
interactions=None,
interactionPairs=None,
earlyStopping=True,
modelId=None,
keepCrossValidationPredictions=False,
keepCrossValidationFoldAssignment=False,
parallelizeCrossValidation=True,
distribution="AUTO",
labelCol="label",
foldCol=None,
weightCol=None,
splitRatio=1.0,
seed=-1,
nfolds=0,
allStringColumnsToCategorical=True,
columnsToCategorical=[],
predictionCol="prediction",
detailedPredictionCol="detailed_prediction",
withDetailedPredictionCol=False,
featuresCols=[],
convertUnknownCategoricalLevelsToNa=False,
convertInvalidNumbersToNa=False,
namedMojoOutputColumns=True,
**DeprecatedParams):
Initializer.load_sparkling_jar()
super(H2OGLM, self).__init__()
self._java_obj = self._new_java_obj("ai.h2o.sparkling.ml.algos.H2OGLM", self.uid)
self._setDefaultValuesFromJava()
kwargs = Utils.getInputKwargs(self)
Utils.propagateValueFromDeprecatedProperty(kwargs, "alpha", "alphaValue")
Utils.propagateValueFromDeprecatedProperty(kwargs, "lambda_", "lambdaValue")
self._set(**kwargs)
def __init__(self,
quietMode=True,
ntrees=50,
nEstimators=0,
maxDepth=6,
minRows=1.0,
minChildWeight=1.0,
learnRate=0.3,
eta=0.3,
learnRateAnnealing=1.0,
sampleRate=1.0,
subsample=1.0,
colSampleRate=1.0,
colSampleByLevel=1.0,
colSampleRatePerTree=1.0,
colSampleByTree=1.0,
maxAbsLeafnodePred=0.0,
maxDeltaStep=0.0,
scoreTreeInterval=0,
initialScoreInterval=4000,
scoreInterval=4000,
minSplitImprovement=0.0,
gamma=0.0,
nthread=-1,
maxBins=256,
maxLeaves=0,
minSumHessianInLeaf=100.0,
minDataInLeaf=0.0,
treeMethod="auto",
growPolicy="depthwise",
booster="gbtree",
dmatrixType="auto",
regLambda=0.0,
regAlpha=0.0,
sampleType="uniform",
normalizeType="tree",
rateDrop=0.0,
oneDrop=False,
skipDrop=0.0,
gpuId=0,
backend="auto",
modelId=None,
keepCrossValidationPredictions=False,
keepCrossValidationFoldAssignment=False,
parallelizeCrossValidation=True,
distribution="AUTO",
labelCol="label",
foldCol=None,
weightCol=None,
splitRatio=1.0,
seed=-1,
nfolds=0,
allStringColumnsToCategorical=True,
columnsToCategorical=[],
predictionCol="prediction",
detailedPredictionCol="detailed_prediction",
withDetailedPredictionCol=False,
featuresCols=[],
convertUnknownCategoricalLevelsToNa=False,
convertInvalidNumbersToNa=False,
**DeprecatedArgs):
Initializer.load_sparkling_jar()
super(H2OXGBoost, self).__init__()
self._java_obj = self._new_java_obj("ai.h2o.sparkling.ml.algos.H2OXGBoost", self.uid)
self._setDefaultValuesFromJava()
kwargs = Utils.getInputKwargs(self)
Utils.propagateValueFromDeprecatedProperty(kwargs, "colsampleBytree", "colSampleByTree")
self._set(**kwargs)