Object/Class

com.databricks.labs.automl.model.tools

GenerationOptimizer

Related Docs: class GenerationOptimizer | package tools

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object GenerationOptimizer extends Serializable

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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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    protected[java.lang]
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  6. def decisionTreesCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[TreesConfig]

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

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )

  10. def gbtCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[GBTConfig]

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

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. def lightGBMCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[LightGBMConfig]

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  15. def linearRegressionCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[LinearRegressionConfig]

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  16. def logisticRegressionCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[LogisticRegressionConfig]

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  17. def mlpcCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int, inputFeatures: Int, distinctClasses: Int)(implicit c: ClassTag[A]): Array[MLPCConfig]

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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. def randomForestCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[RandomForestConfig]

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  22. def svmCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[SVMConfig]

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

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  24. def toString(): String

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  25. final def wait(): Unit

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

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

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  28. def xgBoostCandidates[A, B](modelType: String, regressorType: String, history: ArrayBuffer[A], candidates: Array[B], optimizationType: String, candidateCount: Int)(implicit c: ClassTag[A]): Array[XGBoostConfig]

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