Index

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All Classes|All Packages|Constant Field Values

P

P - Enum constant in enum class com.jml.classifiers.ClassifierTags

PARAMETERS - Enum constant in enum class com.jml.linear_models.LinearModelTags

Perceptron - Class in com.jml.linear_models

A perceptron is a linear model that is equivalent to a single layer neural network.

When a perceptron model is saved, it will be saved as a neural network model.

Perceptron() - Constructor for class com.jml.linear_models.Perceptron

Creates a perceptron with default hyper-parameters.

Perceptron(double, int, int, double) - Constructor for class com.jml.linear_models.Perceptron

Creates a perceptron with specified hyper-parameters and the sigmoid activation function.

Perceptron(double, int, int, double, ActivationFunction) - Constructor for class com.jml.linear_models.Perceptron

Creates a perceptron with specified hyper-parameters and activation function.

PERCEPTRON - Enum constant in enum class com.jml.core.ModelTypes

POLYNOMIAL_REGRESSION - Enum constant in enum class com.jml.core.ModelTypes

POLYNOMIAL_REGRESSION_SGD - Enum constant in enum class com.jml.core.ModelTypes

PolynomialRegression - Class in com.jml.linear_models

Model for least squares linear regression of polynomials.

PolynomialRegression fits a model y = b₀ + b₁x + b₂x² + ...

PolynomialRegression() - Constructor for class com.jml.linear_models.PolynomialRegression

Creates a default polynomial regression model.

PolynomialRegression(int) - Constructor for class com.jml.linear_models.PolynomialRegression

Creates a polynomial regression model with specified degree.

PolynomialRegressionSGD - Class in com.jml.linear_models

Model for least squares regression of polynomials using Stochastic Gradient Descent.

PolynomialRegression fits a model y = b₀ + b₁x + b₂x² + ...

PolynomialRegressionSGD() - Constructor for class com.jml.linear_models.PolynomialRegressionSGD

Creates a PolynomialRegressionSGD model.

PolynomialRegressionSGD(int) - Constructor for class com.jml.linear_models.PolynomialRegressionSGD

Creates a PolynomialRegressionSGD model.

PolynomialRegressionSGD(int, double) - Constructor for class com.jml.linear_models.PolynomialRegressionSGD

Creates a PolynomialRegressionSGD model.

PolynomialRegressionSGD(int, double, int) - Constructor for class com.jml.linear_models.PolynomialRegressionSGD

Creates a PolynomialRegressionSGD model.

PolynomialRegressionSGD(int, double, int, double) - Constructor for class com.jml.linear_models.PolynomialRegressionSGD

Creates a PolynomialRegressionSGD model.

predict(double[]) - Method in class com.jml.linear_models.PolynomialRegression

Uses fitted/trained model to make prediction on single feature.

predict(double[][]) - Method in class com.jml.classifiers.KNearestNeighbors

Uses fitted/trained model to make prediction on single feature.

predict(double[][]) - Method in class com.jml.classifiers.LogisticRegression

Uses fitted/trained model to make prediction on single feature.

predict(double[][]) - Method in class com.jml.linear_models.MultipleLinearRegression

Uses fitted/trained model to make prediction on single feature.

predict(double[][]) - Method in class com.jml.linear_models.Perceptron

Uses fitted/trained model to make prediction on single feature.

predict(double[][]) - Method in class com.jml.neural_network.NeuralNetwork

Uses fitted/trained model to make predictions on features.

predict(Matrix, Matrix) - Method in class com.jml.classifiers.KNearestNeighbors

Makes a prediction using a model by specifying the parameters of the model.

predict(Matrix, Matrix) - Method in class com.jml.classifiers.LogisticRegression

Makes a prediction using a model by specifying the parameters of the model.

predict(Matrix, Matrix) - Method in class com.jml.core.Model

Makes a prediction using a model by specifying the parameters of the model.

predict(Matrix, Matrix) - Method in class com.jml.linear_models.MultipleLinearRegression

Makes a prediction using a model by specifying the parameters of the model.

predict(Matrix, Matrix) - Method in class com.jml.linear_models.Perceptron

Makes a prediction using a model by specifying the parameters of the model.

predict(Matrix, Matrix) - Method in class com.jml.linear_models.PolynomialRegression

Makes a prediction using a model by specifying the parameters of the model.

predict(Matrix, Matrix) - Method in class com.jml.neural_network.NeuralNetwork

Makes a prediction using a model by specifying the parameters of the model.

predict(X) - Method in class com.jml.core.Model

Uses fitted/trained model to make prediction on single feature.

PROBABILITY - Enum constant in enum class com.jml.neural_network.ModelTags

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