GaussianMixtureModelEstimator

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

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3. final def ##(): Int

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11. def fit(samples: Array[DenseVector[Double]]): GaussianMixtureModel

    Fit a Gaussian mixture model with k centers to a sample array.

    Fit a Gaussian mixture model with k centers to a sample array.

    samples

    Sample Array - all elements must be the same size.

    returns

    A Gaussian Mixture Model.

12. def fit(samples: RDD[DenseVector[Double]]): GaussianMixtureModel

    Currently this model works on items that fit in local memory.

    Currently this model works on items that fit in local memory.

    samples

    returns

    A PipelineNode (Transformer) which can be called on new data.

    Definition Classes

    GaussianMixtureModelEstimator → Estimator

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

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22. final def wait(): Unit

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25. def withData(data: RDD[DenseVector[Double]]): Pipeline[DenseVector[Double], DenseVector[Double]]

    Constructs a pipeline from a single estimator and training data.

    Constructs a pipeline from a single estimator and training data. Equivalent to Pipeline() andThen (estimator, data)

    data

    The training data

    Definition Classes

    Estimator