DefaultHyperparams

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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6. 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

7. 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

8. 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

9. 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

10. 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

11. 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.

12. final def eq(arg0: AnyRef): Boolean

    

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13. def equals(arg0: Any): Boolean

    

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14. def finalize(): Unit

    

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15. final def getClass(): Class[_]

    

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16. def hashCode(): Int

    

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17. final def isInstanceOf[T0]: Boolean

    

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18. final def ne(arg0: AnyRef): Boolean

    

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19. final def notify(): Unit

    

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20. final def notifyAll(): Unit

    

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21. final def synchronized[T0](arg0: ⇒ T0): T0

    

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22. def toString(): String

    

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23. final def wait(): Unit

    

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24. final def wait(arg0: Long, arg1: Int): Unit

    

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25. final def wait(arg0: Long): Unit

    

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