class H2OAutoMLParams(H2OCommonSupervisedParams, HasMonotoneConstraints):
##
# Param definitions
##
ignoredCols = Param(
Params._dummy(),
"ignoredCols",
"Ignored column names",
H2OTypeConverters.toListString())
includeAlgos = Param(
Params._dummy(),
"includeAlgos",
"Algorithms to include when using automl",
H2OTypeConverters.toEnumListString("ai.h2o.automl.Algo"))
excludeAlgos = Param(
Params._dummy(),
"excludeAlgos",
"Algorithms to exclude when using automl",
H2OTypeConverters.toEnumListString("ai.h2o.automl.Algo"))
projectName = Param(
Params._dummy(),
"projectName",
"identifier for models that should be grouped together in the leaderboard "
"(e.g., airlines and iris)",
H2OTypeConverters.toNullableString())
maxRuntimeSecs = Param(
Params._dummy(),
"maxRuntimeSecs",
"Maximum time in seconds for automl to be running",
H2OTypeConverters.toFloat())
stoppingRounds = Param(
Params._dummy(),
"stoppingRounds",
"Stopping rounds",
H2OTypeConverters.toInt())
stoppingTolerance = Param(
Params._dummy(),
"stoppingTolerance",
"Stopping tolerance",
H2OTypeConverters.toFloat())
stoppingMetric = Param(
Params._dummy(),
"stoppingMetric",
"Stopping metric",
H2OTypeConverters.toEnumString("hex.ScoreKeeper$StoppingMetric"))
sortMetric = Param(
Params._dummy(),
"sortMetric",
"Sort metric for the AutoML leaderboard",
H2OTypeConverters.toEnumString("ai.h2o.sparkling.ml.algos.H2OAutoMLSortMetric"))
balanceClasses = Param(
Params._dummy(),
"balanceClasses",
"Balance classes",
H2OTypeConverters.toBoolean())
classSamplingFactors = Param(
Params._dummy(),
"classSamplingFactors",
"Class sampling factors",
H2OTypeConverters.toNullableListFloat())
maxAfterBalanceSize = Param(
Params._dummy(),
"maxAfterBalanceSize",
"Max after balance size",
H2OTypeConverters.toFloat())
keepCrossValidationPredictions = Param(
Params._dummy(),
"keepCrossValidationPredictions",
"Keep cross validation predictions",
H2OTypeConverters.toBoolean())
keepCrossValidationModels = Param(
Params._dummy(),
"keepCrossValidationModels",
"Keep cross validation models",
H2OTypeConverters.toBoolean())
maxModels = Param(
Params._dummy(),
"maxModels",
"Max models to train in AutoML",
H2OTypeConverters.toInt())
##
# Getters
##
def getIgnoredCols(self):
return self.getOrDefault(self.ignoredCols)
def getTryMutations(self):
return self.getOrDefault(self.tryMutations)
def getExcludeAlgos(self):
return self.getOrDefault(self.excludeAlgos)
def getIncludeAlgos(self):
return self.getOrDefault(self.includeAlgos)
def getProjectName(self):
return self.getOrDefault(self.projectName)
def getMaxRuntimeSecs(self):
return self.getOrDefault(self.maxRuntimeSecs)
def getStoppingRounds(self):
return self.getOrDefault(self.stoppingRounds)
def getStoppingTolerance(self):
return self.getOrDefault(self.stoppingTolerance)
def getStoppingMetric(self):
return self.getOrDefault(self.stoppingMetric)
def getSortMetric(self):
return self.getOrDefault(self.sortMetric)
def getBalanceClasses(self):
return self.getOrDefault(self.balanceClasses)
def getClassSamplingFactors(self):
return self.getOrDefault(self.classSamplingFactors)
def getMaxAfterBalanceSize(self):
return self.getOrDefault(self.maxAfterBalanceSize)
def getKeepCrossValidationPredictions(self):
return self.getOrDefault(self.keepCrossValidationPredictions)
def getKeepCrossValidationModels(self):
return self.getOrDefault(self.keepCrossValidationModels)
def getMaxModels(self):
return self.getOrDefault(self.maxModels)
##
# Setters
##
def setIgnoredCols(self, value):
return self._set(ignoredCols=value)
def setTryMutations(self, value):
return self._set(tryMutations=value)
def setIncludeAlgos(self, value):
return self._set(includeAlgos=value)
def setExcludeAlgos(self, value):
return self._set(excludeAlgos=value)
def setProjectName(self, value):
return self._set(projectName=value)
def setMaxRuntimeSecs(self, value):
return self._set(maxRuntimeSecs=value)
def setStoppingRounds(self, value):
return self._set(stoppingRounds=value)
def setStoppingTolerance(self, value):
return self._set(stoppingTolerance=value)
def setStoppingMetric(self, value):
return self._set(stoppingMetric=value)
def setSortMetric(self, value):
return self._set(sortMetric=value)
def setBalanceClasses(self, value):
return self._set(balanceClasses=value)
def setClassSamplingFactors(self, value):
return self._set(classSamplingFactors=value)
def setMaxAfterBalanceSize(self, value):
return self._set(maxAfterBalanceSize=value)
def setKeepCrossValidationPredictions(self, value):
return self._set(keepCrossValidationPredictions=value)
def setKeepCrossValidationModels(self, value):
return self._set(keepCrossValidationModels=value)
def setMaxModels(self, value):
return self._set(maxModels=value)
class H2OAutoMLParams(H2OCommonSupervisedParams, HasMonotoneConstraints):
##
# Param definitions
##
ignoredCols = Param(
Params._dummy(),
"ignoredCols",
"Ignored column names",
H2OTypeConverters.toNullableListString())
includeAlgos = Param(
Params._dummy(),
"includeAlgos",
"Algorithms to include when using automl",
H2OTypeConverters.toEnumListString("ai.h2o.automl.Algo", True))
excludeAlgos = Param(
Params._dummy(),
"excludeAlgos",
"Algorithms to exclude when using automl",
H2OTypeConverters.toEnumListString("ai.h2o.automl.Algo", True))
projectName = Param(
Params._dummy(),
"projectName",
"identifier for models that should be grouped together in the leaderboard "
"(e.g., airlines and iris)",
H2OTypeConverters.toNullableString())
maxRuntimeSecs = Param(
Params._dummy(),
"maxRuntimeSecs",
"Maximum time in seconds for automl to be running",
H2OTypeConverters.toFloat())
stoppingRounds = Param(
Params._dummy(),
"stoppingRounds",
"Stopping rounds",
H2OTypeConverters.toInt())
stoppingTolerance = Param(
Params._dummy(),
"stoppingTolerance",
"Stopping tolerance",
H2OTypeConverters.toFloat())
stoppingMetric = Param(
Params._dummy(),
"stoppingMetric",
"Stopping metric",
H2OTypeConverters.toEnumString("hex.ScoreKeeper$StoppingMetric"))
sortMetric = Param(
Params._dummy(),
"sortMetric",
"Sort metric for the AutoML leaderboard",
H2OTypeConverters.toEnumString("ai.h2o.sparkling.ml.utils.H2OAutoMLSortMetric"))
balanceClasses = Param(
Params._dummy(),
"balanceClasses",
"Balance classes",
H2OTypeConverters.toBoolean())
classSamplingFactors = Param(
Params._dummy(),
"classSamplingFactors",
"Class sampling factors",
H2OTypeConverters.toNullableListFloat())
maxAfterBalanceSize = Param(
Params._dummy(),
"maxAfterBalanceSize",
"Max after balance size",
H2OTypeConverters.toFloat())
keepCrossValidationPredictions = Param(
Params._dummy(),
"keepCrossValidationPredictions",
"Keep cross validation predictions",
H2OTypeConverters.toBoolean())
keepCrossValidationModels = Param(
Params._dummy(),
"keepCrossValidationModels",
"Keep cross validation models",
H2OTypeConverters.toBoolean())
keepCrossValidationFoldAssignment = Param(
Params._dummy(),
"keepCrossValidationFoldAssignment",
"Whether to keep cross-validation assignments.",
H2OTypeConverters.toBoolean())
maxModels = Param(
Params._dummy(),
"maxModels",
"Max models to train in AutoML",
H2OTypeConverters.toInt())
maxRuntimeSecsPerModel = Param(
Params._dummy(),
"maxRuntimeSecsPerModel",
"Maximum time to spend on each individual model (optional).",
H2OTypeConverters.toFloat())
exportCheckpointsDir = Param(
Params._dummy(),
"exportCheckpointsDir",
"Path to a directory where every generated model will be stored.",
H2OTypeConverters.toNullableString())
exploitationRatio = Param(
Params._dummy(),
"exploitationRatio",
"The budget ratio (between 0 and 1) dedicated to the exploitation (vs exploration) phase.",
H2OTypeConverters.toFloat())
##
# Getters
##
def getIgnoredCols(self):
return self.getOrDefault(self.ignoredCols)
def getTryMutations(self):
return self.getOrDefault(self.tryMutations)
def getExcludeAlgos(self):
return self.getOrDefault(self.excludeAlgos)
def getIncludeAlgos(self):
return self.getOrDefault(self.includeAlgos)
def getProjectName(self):
return self.getOrDefault(self.projectName)
def getMaxRuntimeSecs(self):
return self.getOrDefault(self.maxRuntimeSecs)
def getStoppingRounds(self):
return self.getOrDefault(self.stoppingRounds)
def getStoppingTolerance(self):
return self.getOrDefault(self.stoppingTolerance)
def getStoppingMetric(self):
return self.getOrDefault(self.stoppingMetric)
def getSortMetric(self):
return self.getOrDefault(self.sortMetric)
def getBalanceClasses(self):
return self.getOrDefault(self.balanceClasses)
def getClassSamplingFactors(self):
return self.getOrDefault(self.classSamplingFactors)
def getMaxAfterBalanceSize(self):
return self.getOrDefault(self.maxAfterBalanceSize)
def getKeepCrossValidationPredictions(self):
return self.getOrDefault(self.keepCrossValidationPredictions)
def getKeepCrossValidationModels(self):
return self.getOrDefault(self.keepCrossValidationModels)
def getKeepCrossValidationFoldAssignment(self):
return self.getOrDefault(self.keepCrossValidationFoldAssignment)
def getMaxModels(self):
return self.getOrDefault(self.maxModels)
def getMaxRuntimeSecsPerModel(self):
return self.getOrDefault(self.maxRuntimeSecsPerModel)
def getExportCheckpointsDir(self):
return self.getOrDefault(self.exportCheckpointsDir)
def getExploitationRatio(self):
return self.getOrDefault(self.exploitationRatio)
##
# Setters
##
def setIgnoredCols(self, value):
return self._set(ignoredCols=value)
def setTryMutations(self, value):
return self._set(tryMutations=value)
def setIncludeAlgos(self, value):
return self._set(includeAlgos=value)
def setExcludeAlgos(self, value):
return self._set(excludeAlgos=value)
def setProjectName(self, value):
return self._set(projectName=value)
def setMaxRuntimeSecs(self, value):
return self._set(maxRuntimeSecs=value)
def setStoppingRounds(self, value):
return self._set(stoppingRounds=value)
def setStoppingTolerance(self, value):
return self._set(stoppingTolerance=value)
def setStoppingMetric(self, value):
return self._set(stoppingMetric=value)
def setSortMetric(self, value):
return self._set(sortMetric=value)
def setBalanceClasses(self, value):
return self._set(balanceClasses=value)
def setClassSamplingFactors(self, value):
return self._set(classSamplingFactors=value)
def setMaxAfterBalanceSize(self, value):
return self._set(maxAfterBalanceSize=value)
def setKeepCrossValidationPredictions(self, value):
return self._set(keepCrossValidationPredictions=value)
def setKeepCrossValidationModels(self, value):
return self._set(keepCrossValidationModels=value)
def setKeepCrossValidationFoldAssignment(self, value):
return self._set(keepCrossValidationFoldAssignment=value)
def setMaxModels(self, value):
return self._set(maxModels=value)
def setMaxRuntimeSecsPerModel(self, value):
return self._set(maxRuntimeSecsPerModel=value)
def setExportCheckpointsDir(self, value):
return self._set(exportCheckpointsDir=value)
def setExploitationRatio(self, value):
return self._set(exploitationRatio=value)