Index

A B C D E F G H I K L M N O P R S T U V W Z
All Classes|All Packages|Constant Field Values

L

l1(double[]) - Static method in class com.jml.preprocessing.Normalize

Normalizes the data by subtracting the mean and dividing by the L1-norm.

l2(double[]) - Static method in class com.jml.preprocessing.Normalize

Normalizes the data by subtracting the mean and dividing by the L2-norm.

l2(double[][]) - Static method in class com.jml.preprocessing.Normalize

Normalizes each column of the data by subtracting the mean of that column and dividing by the L2-norm of that column.

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

LAYER_TYPE - Variable in class com.jml.neural_network.layers.Dense

LAYER_TYPE - Variable in class com.jml.neural_network.layers.Dropout

LAYER_TYPE - Variable in class com.jml.neural_network.layers.Linear

linear - Static variable in class com.jml.neural_network.activations.Activations

A pre-defined instance of the linear activation function.

linear() - Static method in class com.jml.neural_network.activations.Activations

Creates and returns a new instacne of the linear activation function.

Linear - Class in com.jml.neural_network.activations

The linear activation function.

Linear - Class in com.jml.neural_network.layers

Simple fully-connected linear layer.

Linear() - Constructor for class com.jml.neural_network.activations.Linear

Linear(int) - Constructor for class com.jml.neural_network.layers.Linear

Creates a Linear layer with specified input and output dimensions.
NOTE: this constructor infers the input dimension from the previous layer in the network.

Linear(int, int) - Constructor for class com.jml.neural_network.layers.Linear

Creates a Linear layer with specified input and output dimensions.

Linear(int, int, Initializer) - Constructor for class com.jml.neural_network.layers.Linear

Creates a Linear layer with specified input and output dimensions.

Linear(int, int, Initializer, Initializer) - Constructor for class com.jml.neural_network.layers.Linear

Creates a Linear layer with specified input and output dimensions.

Linear(int, Initializer) - Constructor for class com.jml.neural_network.layers.Linear

Creates a Linear layer with specified input and output dimensions.
NOTE: this constructor infers the input dimension from the previous layer in the network.

Linear(int, Initializer, Initializer) - Constructor for class com.jml.neural_network.layers.Linear

Creates a Linear layer with specified input and output dimensions.
NOTE: this constructor infers the input dimension from the previous layer in the network.

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

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

LinearModelTags - Enum Class in com.jml.linear_models

LinearRegression - Class in com.jml.linear_models

Model for ordinary least squares linear regression of one variable.

LinearRegression fits a model y = b₀ + b₁x to the datasets by minimizing the residuals of the sum of squares between the values in the target dataset and the values predicted by the model.

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

LinearRegressionSGD - Class in com.jml.linear_models

Model for least squares linear regression of one variable by stochastic gradient descent.

LinearRegressionSGD fits a model y = b₀ + b₁x to the datasets by minimizing the residuals of the sum of squares between the values in the target dataset and the values predicted by the model.

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

Creates a LinearRegressionSGD model.
This will use default settings for gradient descent:

LinearRegressionSGD(double) - Constructor for class com.jml.linear_models.LinearRegressionSGD

Creates a LinearRegressionSGD model.

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

Creates a LinearRegressionSGD model.

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

Creates a LinearRegressionSGD model.

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

Creates a LinearRegressionSGD model.

load(String) - Static method in class com.jml.core.Model

Loads a model from specified file path including extension.
Models must be saved as an MDL file (i.e.

loadFeaturesAndTargets(String) - Static method in class com.jml.core.DataLoader

Loads targets and features from a csv file.

loadFeaturesAndTargets(String, int[], int[]) - Static method in class com.jml.core.DataLoader

Loads targets and features from a csv file.

The csv file is assumed to have one data sample per row.

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

LogisticRegression - Class in com.jml.classifiers

A logistic regression model.

LogisticRegression() - Constructor for class com.jml.classifiers.LogisticRegression

Creates a logistic regression model.

LogisticRegression(double) - Constructor for class com.jml.classifiers.LogisticRegression

Creates a logistic regression model.

LogisticRegression(double, int) - Constructor for class com.jml.classifiers.LogisticRegression

Creates a logistic regression model.

LogisticRegression(double, int, double) - Constructor for class com.jml.classifiers.LogisticRegression

Creates a logistic regression model.

LossFunctions - Class in com.jml.losses

This class contains lambda functions for various loss functions including:

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