A B C D E F G H I J L M N O P R S T U W X Y
All Classes All Packages

M

main(String[]) - Static method in class me.yixqiao.jlearn.testing.Genetic

Run.

main(String[]) - Static method in class me.yixqiao.jlearn.testing.Iris

Run.

main(String[]) - Static method in class me.yixqiao.jlearn.testing.MNIST

Run.

main(String[]) - Static method in class me.yixqiao.jlearn.testing.MNISTSave

Run.

main(String[]) - Static method in class me.yixqiao.jlearn.testing.XOR

Run.

mat - Variable in class me.yixqiao.jlearn.matrix.Matrix

Contains the matrix itself.

Matrix - Class in me.yixqiao.jlearn.matrix

Matrix class and operations.

Matrix(double[][]) - Constructor for class me.yixqiao.jlearn.matrix.Matrix

Create a matrix from an existing 2d array of doubles.

Matrix(int, int) - Constructor for class me.yixqiao.jlearn.matrix.Matrix

Creates a new, empty matrix.

Matrix(int, int, Matrix.Init) - Constructor for class me.yixqiao.jlearn.matrix.Matrix

Create a new matrix using an Matrix.Init object.

Matrix.Init - Class in me.yixqiao.jlearn.matrix

Initialization methods for Matrix.

Matrix.Init.Empty - Class in me.yixqiao.jlearn.matrix

Init all with 0s.

Matrix.Init.Fill - Class in me.yixqiao.jlearn.matrix

Init all with a number.

Matrix.Init.Gaussian - Class in me.yixqiao.jlearn.matrix

Generate random numbers from the gaussian distribution to fill the matrix.

Matrix.Init.Uniform - Class in me.yixqiao.jlearn.matrix

Generate a uniform range of random numbers to fill the matrix.

MatrixMathException - Exception in me.yixqiao.jlearn.exceptions

Exception when executing matrix math.

MatrixMathException() - Constructor for exception me.yixqiao.jlearn.exceptions.MatrixMathException

Create an exception.

MatrixMathException(String) - Constructor for exception me.yixqiao.jlearn.exceptions.MatrixMathException

Create an exception.

me.yixqiao.jlearn.activations - package me.yixqiao.jlearn.activations

Various activations for each layer.

me.yixqiao.jlearn.datasets - package me.yixqiao.jlearn.datasets

Datasets and helper functions.

me.yixqiao.jlearn.exceptions - package me.yixqiao.jlearn.exceptions

Package containing exceptions.

me.yixqiao.jlearn.genetic - package me.yixqiao.jlearn.genetic

Genetic algorithms.

me.yixqiao.jlearn.initializers - package me.yixqiao.jlearn.initializers

Various initialization methods for weights.

me.yixqiao.jlearn.layers - package me.yixqiao.jlearn.layers

Various layers to use in the network.

me.yixqiao.jlearn.losses - package me.yixqiao.jlearn.losses

Various losses to use in training.

me.yixqiao.jlearn.matrix - package me.yixqiao.jlearn.matrix

Contains the Matrix class.

me.yixqiao.jlearn.metrics - package me.yixqiao.jlearn.metrics

Metrics to evaulate the model.

me.yixqiao.jlearn.models - package me.yixqiao.jlearn.models

Contains model architectures.

me.yixqiao.jlearn.optimizers - package me.yixqiao.jlearn.optimizers

Various optimizers for training.

me.yixqiao.jlearn.settings - package me.yixqiao.jlearn.settings

Global settings for JLearn.

me.yixqiao.jlearn.testing - package me.yixqiao.jlearn.testing

Some runnable classes for testing the library.

MeanSquaredError - Class in me.yixqiao.jlearn.losses

Mean squared error loss.

MeanSquaredError() - Constructor for class me.yixqiao.jlearn.losses.MeanSquaredError

Metric - Class in me.yixqiao.jlearn.metrics

Class for a metric.

Metric() - Constructor for class me.yixqiao.jlearn.metrics.Metric

metrics - Variable in class me.yixqiao.jlearn.models.Model.FitBuilder

Metrics to gauge model performance.

metrics(ArrayList<Metric>) - Method in class me.yixqiao.jlearn.models.Model.FitBuilder

Set metrics.

MNIST - Class in me.yixqiao.jlearn.testing

Train a network on the MNIST digits dataset.

MNIST() - Constructor for class me.yixqiao.jlearn.testing.MNIST

MNISTDigits - Class in me.yixqiao.jlearn.datasets

Class for the MNIST digits dataset.

MNISTDigits() - Constructor for class me.yixqiao.jlearn.datasets.MNISTDigits

MNISTSave - Class in me.yixqiao.jlearn.testing

Train a model on the MNIST dataset, then save it to a file and load it back to evaluate.

MNISTSave() - Constructor for class me.yixqiao.jlearn.testing.MNISTSave

model - Variable in class me.yixqiao.jlearn.testing.MNIST

Model.

Model - Class in me.yixqiao.jlearn.models

Neural network model.

Model() - Constructor for class me.yixqiao.jlearn.models.Model

Create a new model.

Model.FitBuilder - Class in me.yixqiao.jlearn.models

Builder class for fit operation.

Model.FitPrint - Class in me.yixqiao.jlearn.models

Thread to print progress when fitting.

Momentum - Class in me.yixqiao.jlearn.optimizers

Gradient descent with momentum.

Momentum(double, double) - Constructor for class me.yixqiao.jlearn.optimizers.Momentum

Create a new instance.

multiply(double) - Method in class me.yixqiao.jlearn.matrix.Matrix

Multiply each matrix element by a scalar.

multiply(Matrix) - Method in class me.yixqiao.jlearn.matrix.Matrix

Multiply by another matrix element by element.

multiplyIP(double) - Method in class me.yixqiao.jlearn.matrix.Matrix

Multiply each matrix element by a scalar, in place.

multiplyIP(Matrix) - Method in class me.yixqiao.jlearn.matrix.Matrix

Multiply by another matrix element by element, in place.

multiplyLR(double) - Method in class me.yixqiao.jlearn.optimizers.Adam

multiplyLR(double) - Method in class me.yixqiao.jlearn.optimizers.Momentum

multiplyLR(double) - Method in class me.yixqiao.jlearn.optimizers.Optimizer

Multiply the learning rate.

multiplyLR(double) - Method in class me.yixqiao.jlearn.optimizers.SGD

A B C D E F G H I J L M N O P R S T U W X Y
All Classes All Packages