Classification Models

Classification Models API Reference

Functions

GaussianDiscriminant(M, X, Y; Factors = nothing)

Returns a GaussianDiscriminant classification model on basis object M (PCA, LDA) and one hot encoded Y.

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( model::GaussianDiscriminant )( Z; Factors = size(model.ProjectedClassMeans)[2] )

Returns a 1 hot encoded inference from Z using a GaussianDiscriminant object.

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GaussianNaiveBayes(X,Y)

Returns a GaussianNaiveBayes classification model object from X and one hot encoded Y.

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(gnb::GaussianNaiveBayes)(X)

Returns a 1 hot encoded inference from X using a GaussianNaiveBayes object.

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KNN( X, Y; DistanceType::String )

DistanceType can be "euclidean", "manhattan". Y Must be one hot encoded.

Returns a KNN classification model.

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( model::KNN )( Z; K = 1 )

Returns a 1 hot encoded inference from X with K Nearest Neighbors, using a KNN object.

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( model::LogisticRegression )( X )

Returns a 1 hot encoded inference from X using a LogisticRegression object.

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ProbabilisticNeuralNetwork( X, Y )

Stores data for a PNN. Y Must be one hot encoded.

Returns a PNN classification model.

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(PNN::ProbabilisticNeuralNetwork)(X; sigma = 0.1)

Returns a 1 hot encoded inference from X with a probabilistic neural network.

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MultinomialSoftmaxRegression(X, Y; LearnRate = 1e-3, maxiters = 1000, L2 = 0.0)

Returns a LogisticRegression classification model made by Stochastic Gradient Descent.

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