object DefaultHyperparams
Provides good default hyperparameter ranges and values for sweeping. Publicly visible to users so they can easily select the parameters for sweeping.
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def
defaultRange(learner: NaiveBayes): Array[(Param[_], Dist[_])]
Defines the default hyperparameter range for naive bayes classifier
Defines the default hyperparameter range for naive bayes classifier
- returns
The hyperparameter search space for naive bayes classifier
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def
defaultRange(learner: MultilayerPerceptronClassifier): Array[(Param[_], Dist[_])]
Defines the default hyperparameter range for multilayer perceptron classifier
Defines the default hyperparameter range for multilayer perceptron classifier
- returns
The hyperparameter search space for multilayer perceptron classifier
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def
defaultRange(learner: RandomForestClassifier): Array[(Param[_], Dist[_])]
Defines the default hyperparameter range for random forest classifier
Defines the default hyperparameter range for random forest classifier
- returns
The hyperparameter search space for random forest classifier
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def
defaultRange(learner: GBTClassifier): Array[(Param[_], Dist[_])]
Defines the default hyperparameter range for gradient boosted trees classifier
Defines the default hyperparameter range for gradient boosted trees classifier
- returns
The hyperparameter search space for gradient boosted trees classifier
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def
defaultRange(learner: DecisionTreeClassifier): Array[(Param[_], Dist[_])]
Defines the default hyperparameter range for decision tree classifier
Defines the default hyperparameter range for decision tree classifier
- returns
The hyperparameter search space for decision tree classifier
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def
defaultRange(learner: LogisticRegression): Array[(Param[_], Dist[_])]
Defines the default hyperparameter range for logistic regression.
Defines the default hyperparameter range for logistic regression.
- returns
The hyperparameter search space for logistic regression.
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