GaussianNB

public class GaussianNB

Gaussian naive bayes classifier.

Gaussian naive bayes classifier used to classify continuous features.

  • Unique classes in target value set.

    Declaration

    Swift

    public var classes: Tensor<Int32>

  • Tensor contains the index of class in classes.

    Declaration

    Swift

    public var indices: Tensor<Int32>

  • The mean and the standard deviation of each feature of each class.

    Declaration

    Swift

    public var model: Tensor<Float>

  • Create a Gaussian naive bayes model.

    Declaration

    Swift

    public init()

  • Fit a Gaussian naive bayes classifier model.

    Declaration

    Swift

    public func fit(data: Tensor<Float>, labels: Tensor<Int32>)

    Parameters

    data

    Training data with shape [sample count, feature count].
    labels

    Target value with shape [sample count].

  • Returns a log of gaussian distribution.

    Declaration

    Swift

    internal func prob(
    data: Tensor<Float>,
    mean: Tensor<Float>,
    std: Tensor<Float>
) -> Tensor<Float>

    Parameters

    data

    Input data to find gausssian distribution.
    mean

    Mean of input tensor.
    std

    Standard deviation of input data.

    Return Value

    Log of gaussian distribution.

  • Returns predict log probability.

    Declaration

    Swift

    public func predictLogProba(data: Tensor<Float>) -> Tensor<Float>

    Parameters

    data

    Input data to predict log probability.

    Return Value

    predicted log probability.

  • Returns classification.

    Declaration

    Swift

    public func prediction(for data: Tensor<Float>) -> Tensor<Int32>

    Parameters

    data

    Input data with shape [sample count, feature count].

    Return Value

    prediction of input data.

  • Returns mean accuracy on the given input data and labels.

    Declaration

    Swift

    public func score(data: Tensor<Float>, labels: Tensor<Int32>) -> Float

    Parameters

    data

    Sample data with shape [sample count, feature count].
    labels

    Target label with shape [sample count].

    Return Value

    Returns the mean accuracy on the given input data and labels.