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au.id.cxd.math.model.components

PrincipleComponentsAnalysis

Related Docs: class PrincipleComponentsAnalysis | package components

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object PrincipleComponentsAnalysis

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

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  2. final def ##(): Int

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  4. def apply(scale: Boolean, X: DenseMatrix[Double]): (DenseVector[Double], DenseMatrix[Double], DenseVector[Double], DenseMatrix[Double])

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    apply PCA to the supplied matrix.

    apply PCA to the supplied matrix.

    scale

    : a flag indicating whether to normalise X

    returns

    * tuple of * (eigenValues, eigenVectors, variance explained, projection of X into the eigenvectors)

  5. def apply(X: DenseMatrix[Double]): (DenseVector[Double], DenseMatrix[Double], DenseVector[Double], DenseMatrix[Double])

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    apply PCA to the supplied matrix.

    apply PCA to the supplied matrix.

    returns

    tuple of (eigenValues, eigenVectors, variance explained, projection of X into the eigenvectors)

  6. final def asInstanceOf[T0]: T0

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  18. def toString(): String

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  19. def varianceExplained(eigenValues: DenseVector[Double]): DenseVector[Double]

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    determine the percent of variance explained by each component.

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