Index (lib 1.0.7 API)

A B C D E F G H I K L M N O P Q R S T U V W X
Alle Klassen und Schnittstellen|Alle Packages|Serialisierte Form

A

AbstractAugmentation - Klasse in de.edux.augmentation.core: Abstract class for augmentation operations.
AbstractAugmentation() - Konstruktor für Klasse de.edux.augmentation.core.AbstractAugmentation
ActivationFunction - Enum-Klasse in de.edux.functions.activation: Enumerates common activation functions used in neural networks and similar machine learning architectures.
addAugmentation(AbstractAugmentation) - Methode in Klasse de.edux.augmentation.core.AugmentationBuilder: Adds an augmentation to the sequence.
addMatrices(double[][], double[][]) - Methode in Schnittstelle de.edux.util.math.MatrixOperations: Adds two matrices and returns the resulting matrix.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.core.AbstractAugmentation: Applies the augmentation to an image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.BlurAugmentation: Applies a Gaussian blur augmentation to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.BrightnessAugmentation: Loop through each image pixel and multiply the pixel value by the brightness value
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.ColorEqualizationAugmentation: Applies color equalization to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.ContrastAugmentation: Applies contrast enhancement to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.CroppingAugmentation: Applies a cropping augmentation to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.ElasticTransformationAugmentation: Applies the elastic transformation to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.FlippingAugmentation: Applies a random flip augmentation to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.MonochromeAugmentation
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.NoiseInjectionAugmentation
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.PerspectiveTransformationsAugmentation: Applies the affine transformation to the provided image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.RandomDeleteAugmentation: Applies the random delete operation to the given image.
apply(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.ResizeAugmentation: Resizes the given image to the target width and height which are either specified during the instantiation or computed based on the scaleFactor.
applyTo(BufferedImage) - Methode in Schnittstelle de.edux.augmentation.core.AugmentationSequence: Applies the augmentation sequence to a single image.
applyTo(BufferedImage) - Methode in Klasse de.edux.augmentation.core.CompositeAugmentationSequence
AugmentationBuilder - Klasse in de.edux.augmentation.core: Builder class for creating an augmentation sequence.
AugmentationBuilder() - Konstruktor für Klasse de.edux.augmentation.core.AugmentationBuilder
AugmentationImageReader - Klasse in de.edux.augmentation.io: Implementation of IAugmentationImageReader to read image paths from a specified directory.
AugmentationImageReader() - Konstruktor für Klasse de.edux.augmentation.io.AugmentationImageReader
AugmentationSequence - Schnittstelle in de.edux.augmentation.core: Defines a sequence of image augmentation operations.
AVERAGE - Enum-Konstante in Enum-Klasse de.edux.functions.imputation.ImputationStrategy: Imputation strategy that replaces missing values with the average of the non-missing values in the dataset column.
AverageImputation - Klasse in de.edux.functions.imputation: Implements the IImputationStrategy interface to provide an average value imputation.
AverageImputation() - Konstruktor für Klasse de.edux.functions.imputation.AverageImputation

B

backpropagate(double[], double) - Methode in Schnittstelle de.edux.ml.nn.network.api.IPerceptron
BALANCED - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.ResizeQuality
BINARY_CROSS_ENTROPY - Enum-Konstante in Enum-Klasse de.edux.functions.loss.LossFunction
BlurAugmentation - Klasse in de.edux.augmentation.effects: This class provides an augmentation that applies a Gaussian blur to an image.
BlurAugmentation(float) - Konstruktor für Klasse de.edux.augmentation.effects.BlurAugmentation: Initializes a new instance of the BlurAugmentation class with the specified blur radius.
BOTTOM_LEFT_CORNER_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
BOTTOM_RIGHT_CORNER_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
BOTTOM_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
BrightnessAugmentation - Klasse in de.edux.augmentation.effects: This augmentation technique adjusts an image's brightness value by a specified amount
BrightnessAugmentation(double) - Konstruktor für Klasse de.edux.augmentation.effects.BrightnessAugmentation: Initialize the class with a double value between -1 and 1 indicating the brightness factor to be applied A value greater than 0 will increase brightness A value lower than 0 will decrease brightness
build() - Methode in Klasse de.edux.augmentation.core.AugmentationBuilder: Builds the final Augmentation sequence from the added operations.

C

calculateActivation(double) - Methode in Enum-Klasse de.edux.functions.activation.ActivationFunction
calculateActivation(double[]) - Methode in Enum-Klasse de.edux.functions.activation.ActivationFunction
calculateDerivative(double) - Methode in Enum-Klasse de.edux.functions.activation.ActivationFunction
calculateError(double) - Methode in Schnittstelle de.edux.ml.nn.network.api.INeuron
calculateError(double[], double[]) - Methode in Enum-Klasse de.edux.functions.loss.LossFunction
calculateOutput(double[]) - Methode in Schnittstelle de.edux.ml.nn.network.api.INeuron
CATEGORICAL_CROSS_ENTROPY - Enum-Konstante in Enum-Klasse de.edux.functions.loss.LossFunction
Classifier - Schnittstelle in de.edux.api: Provides a common interface for machine learning classifiers within the Edux API.
ColorEqualizationAugmentation - Klasse in de.edux.augmentation.effects: This class implements an augmentation that applies color equalization to an image.
ColorEqualizationAugmentation() - Konstruktor für Klasse de.edux.augmentation.effects.ColorEqualizationAugmentation
CompositeAugmentationSequence - Klasse in de.edux.augmentation.core: Composite augmentation that applies a sequence of augmentations.
CompositeAugmentationSequence(List<AbstractAugmentation>) - Konstruktor für Klasse de.edux.augmentation.core.CompositeAugmentationSequence
ConcurrentMatrixMultiplication - Schnittstelle in de.edux.util.math
ContrastAugmentation - Klasse in de.edux.augmentation.effects: This class enhances the contrast of an image.
ContrastAugmentation(float) - Konstruktor für Klasse de.edux.augmentation.effects.ContrastAugmentation: Initializes a new instance of the ContrastAugmentation class with the specified contrast factor.
convert2DLabelArrayTo1DLabelArray(double[][]) - Statische Methode in Klasse de.edux.util.LabelDimensionConverter
CroppingAugmentation - Klasse in de.edux.augmentation.effects: This class provides an augmentation that crops an image based on a specified factor.
CroppingAugmentation(float) - Konstruktor für Klasse de.edux.augmentation.effects.CroppingAugmentation: Constructs a CroppingAugmentation with a specified crop factor.
CSVIDataReader - Klasse in de.edux.data.reader
CSVIDataReader() - Konstruktor für Klasse de.edux.data.reader.CSVIDataReader
CUDAKernelUser - Schnittstelle in de.edux.core.math.matrix.cuda
CudaMatrixArithmetic - Klasse in de.edux.core.math.matrix.cuda
CudaMatrixArithmetic() - Konstruktor für Klasse de.edux.core.math.matrix.cuda.CudaMatrixArithmetic
CudaMatrixProduct - Klasse in de.edux.core.math.matrix.cuda.operations
CudaMatrixProduct() - Konstruktor für Klasse de.edux.core.math.matrix.cuda.operations.CudaMatrixProduct
CudaMatrixVectorProduct - Klasse in de.edux.core.math.matrix.cuda.operations
CudaMatrixVectorProduct() - Konstruktor für Klasse de.edux.core.math.matrix.cuda.operations.CudaMatrixVectorProduct
CudaNotAvailableException - Ausnahmeklasse in de.edux.core.math.matrix.cuda.exceptions
CudaNotAvailableException(String) - Konstruktor für Ausnahmeklasse de.edux.core.math.matrix.cuda.exceptions.CudaNotAvailableException

D

Dataloader - Schnittstelle in de.edux.data.provider: The Dataloader interface defines a method for loading datasets from CSV files.
DataNormalizer - Klasse in de.edux.data.provider
DataNormalizer() - Konstruktor für Klasse de.edux.data.provider.DataNormalizer
DataPostProcessor - Schnittstelle in de.edux.data.provider: The DataPostProcessor interface defines a set of methods for post-processing data.
DataProcessor - Klasse in de.edux.data.provider
DataProcessor(IDataReader) - Konstruktor für Klasse de.edux.data.provider.DataProcessor
Dataset<T> - Datensatzklasse in de.edux.ml.nn.network.api
Dataset - Schnittstelle in de.edux.data.provider
Dataset(List<T>, List<T>) - Konstruktor für Datensatzklasse de.edux.ml.nn.network.api.Dataset: Erstellt eine Instanz einer Datensatzklasse Dataset.
de.edux.api - Package de.edux.api
de.edux.augmentation.core - Package de.edux.augmentation.core: Core functionalities for image augmentation in the Edux framework.
de.edux.augmentation.effects - Package de.edux.augmentation.effects: This package contains classes that perform various image augmentation effects.
de.edux.augmentation.effects.geomentry - Package de.edux.augmentation.effects.geomentry: Provides perspective transformation effects that can be applied to images.
de.edux.augmentation.io - Package de.edux.augmentation.io: Provides classes and interfaces for reading and handling image data for augmentation processes.
de.edux.core.math - Package de.edux.core.math
de.edux.core.math.matrix.cuda - Package de.edux.core.math.matrix.cuda
de.edux.core.math.matrix.cuda.exceptions - Package de.edux.core.math.matrix.cuda.exceptions
de.edux.core.math.matrix.cuda.operations - Package de.edux.core.math.matrix.cuda.operations
de.edux.core.math.matrix.parallel - Package de.edux.core.math.matrix.parallel
de.edux.core.math.matrix.parallel.operations - Package de.edux.core.math.matrix.parallel.operations
de.edux.data.provider - Package de.edux.data.provider
de.edux.data.reader - Package de.edux.data.reader
de.edux.functions.activation - Package de.edux.functions.activation: Provides the classes necessary to define various activation functions used in neural networks.
de.edux.functions.imputation - Package de.edux.functions.imputation
de.edux.functions.initialization - Package de.edux.functions.initialization
de.edux.functions.loss - Package de.edux.functions.loss
de.edux.ml.decisiontree - Package de.edux.ml.decisiontree: Decision tree implementation.
de.edux.ml.knn - Package de.edux.ml.knn: Provides the classes necessary for implementing the k-Nearest Neighbors (KNN) algorithm in machine learning.
de.edux.ml.nn.config - Package de.edux.ml.nn.config: Classes for the configuration of the neural network.
de.edux.ml.nn.network - Package de.edux.ml.nn.network
de.edux.ml.nn.network.api - Package de.edux.ml.nn.network.api
de.edux.ml.randomforest - Package de.edux.ml.randomforest: Random Forest implementation.
de.edux.ml.svm - Package de.edux.ml.svm: Support Vector Machine (SVM) implementation.
de.edux.util - Package de.edux.util
de.edux.util.math - Package de.edux.util.math
DecisionTree - Klasse in de.edux.ml.decisiontree: A Decision Tree classifier for predictive modeling.
DecisionTree(int, int, int, int) - Konstruktor für Klasse de.edux.ml.decisiontree.DecisionTree
determinant(double[][]) - Methode in Schnittstelle de.edux.util.math.MatrixOperations: Calculates and returns the determinant of the given matrix.

E

ElasticTransformationAugmentation - Klasse in de.edux.augmentation.effects: Applies an elastic transformation to an image, simulating natural distortions.
ElasticTransformationAugmentation(double, double) - Konstruktor für Klasse de.edux.augmentation.effects.ElasticTransformationAugmentation: Constructs an ElasticTransformationAugmentation instance with the given parameters.
epochs() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente epochs zurück.
equals(Object) - Methode in Datensatzklasse de.edux.augmentation.io.ImageWithName: Gibt an, ob ein anderes Objekt diesem gleich ("equal to") ist.
equals(Object) - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt an, ob ein anderes Objekt diesem gleich ("equal to") ist.
equals(Object) - Methode in Datensatzklasse de.edux.ml.nn.network.api.Dataset: Gibt an, ob ein anderes Objekt diesem gleich ("equal to") ist.
equals(Object) - Methode in Datensatzklasse de.edux.ml.randomforest.Sample: Gibt an, ob ein anderes Objekt diesem gleich ("equal to") ist.
evaluate(double[][], double[][]) - Methode in Schnittstelle de.edux.api.Classifier: Evaluates the model's performance against the provided test inputs and targets.
evaluate(double[][], double[][]) - Methode in Klasse de.edux.ml.decisiontree.DecisionTree
evaluate(double[][], double[][]) - Methode in Klasse de.edux.ml.knn.KnnClassifier
evaluate(double[][], double[][]) - Methode in Schnittstelle de.edux.ml.nn.network.api.IPerceptron
evaluate(double[][], double[][]) - Methode in Klasse de.edux.ml.nn.network.MultilayerPerceptron
evaluate(double[][], double[][]) - Methode in Klasse de.edux.ml.randomforest.RandomForest
evaluate(double[][], double[][]) - Methode in Klasse de.edux.ml.svm.SupportVectorMachine
evaluate(double[][], int[]) - Methode in Schnittstelle de.edux.ml.svm.ISupportVectorMachine

F

FAST - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.ResizeQuality
featureSamples() - Methode in Datensatzklasse de.edux.ml.randomforest.Sample: Gibt den Wert für die Datensatzkomponente featureSamples zurück.
fileName() - Methode in Datensatzklasse de.edux.augmentation.io.ImageWithName: Gibt den Wert für die Datensatzkomponente fileName zurück.
FlippingAugmentation - Klasse in de.edux.augmentation.effects: This class provides an augmentation that randomly flips an image either horizontally or vertically.
FlippingAugmentation() - Konstruktor für Klasse de.edux.augmentation.effects.FlippingAugmentation

G

getClassMap() - Methode in Klasse de.edux.data.provider.DataProcessor
getClassMap() - Methode in Schnittstelle de.edux.data.provider.Dataset
getColumnDataOf(int) - Methode in Klasse de.edux.data.provider.DataProcessor
getColumnDataOf(int) - Methode in Schnittstelle de.edux.data.provider.Dataset
getDataset() - Methode in Schnittstelle de.edux.data.provider.DataPostProcessor: Retrieves the processed dataset as a list of string arrays.
getDataset() - Methode in Klasse de.edux.data.provider.DataProcessor
getFeatureImportance() - Methode in Schnittstelle de.edux.ml.decisiontree.IDecisionTree: Returns the feature importance of the decision tree.
getFeatureImportances() - Methode in Klasse de.edux.ml.decisiontree.DecisionTree
getImputation() - Methode in Enum-Klasse de.edux.functions.imputation.ImputationStrategy: Retrieves the IImputationStrategy implementation associated with the imputation strategy.
getInputs(List<String[]>, int[]) - Methode in Klasse de.edux.data.provider.DataProcessor
getInputs(List<String[]>, int[]) - Methode in Schnittstelle de.edux.data.provider.Dataset
getScaleX() - Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
getScaleY() - Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
getShearX() - Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
getShearY() - Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
getTargets(List<String[]>, int) - Methode in Klasse de.edux.data.provider.DataProcessor
getTargets(List<String[]>, int) - Methode in Schnittstelle de.edux.data.provider.Dataset
getTestFeatures(int[]) - Methode in Klasse de.edux.data.provider.DataProcessor
getTestFeatures(int[]) - Methode in Schnittstelle de.edux.data.provider.Dataset
getTestLabels(int) - Methode in Klasse de.edux.data.provider.DataProcessor
getTestLabels(int) - Methode in Schnittstelle de.edux.data.provider.Dataset
getTrainFeatures(int[]) - Methode in Klasse de.edux.data.provider.DataProcessor
getTrainFeatures(int[]) - Methode in Schnittstelle de.edux.data.provider.Dataset
getTrainLabels(int) - Methode in Klasse de.edux.data.provider.DataProcessor
getTrainLabels(int) - Methode in Schnittstelle de.edux.data.provider.Dataset
getTranslateX() - Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
getTranslateY() - Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective

H

hashCode() - Methode in Datensatzklasse de.edux.augmentation.io.ImageWithName: Gibt einen Hashcodewert für diese Objekt zurück.
hashCode() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt einen Hashcodewert für diese Objekt zurück.
hashCode() - Methode in Datensatzklasse de.edux.ml.nn.network.api.Dataset: Gibt einen Hashcodewert für diese Objekt zurück.
hashCode() - Methode in Datensatzklasse de.edux.ml.randomforest.Sample: Gibt einen Hashcodewert für diese Objekt zurück.
HE - Enum-Konstante in Enum-Klasse de.edux.functions.initialization.Initialization: He initialization strategy for weights.
hiddenLayerActivationFunction() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente hiddenLayerActivationFunction zurück.
hiddenLayersSize() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente hiddenLayersSize zurück.
hiddenLayerWeightInitialization() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente hiddenLayerWeightInitialization zurück.
HINGE_LOSS - Enum-Konstante in Enum-Klasse de.edux.functions.loss.LossFunction

I

IAugmentationImageReader - Schnittstelle in de.edux.augmentation.io
IDataReader - Schnittstelle in de.edux.data.reader
IDecisionTree - Schnittstelle in de.edux.ml.decisiontree
IImputationStrategy - Schnittstelle in de.edux.functions.imputation: Defines a strategy interface for imputing missing values within a column of data.
image() - Methode in Datensatzklasse de.edux.augmentation.io.ImageWithName: Gibt den Wert für die Datensatzkomponente image zurück.
ImageConsumer - Klasse in de.edux.augmentation.io
ImageConsumer(BlockingQueue<ImageWithName>, AugmentationSequence, String) - Konstruktor für Klasse de.edux.augmentation.io.ImageConsumer
ImageProcessingManager - Klasse in de.edux.augmentation.io
ImageProcessingManager(String, int, AugmentationSequence, String) - Konstruktor für Klasse de.edux.augmentation.io.ImageProcessingManager
ImageProducer - Klasse in de.edux.augmentation.io: Handles the production of images from a specified directory, queuing them for further processing.
ImageProducer(BlockingQueue<ImageWithName>, String, int) - Konstruktor für Klasse de.edux.augmentation.io.ImageProducer: Constructs an ImageProducer with the specified queue, directory path, and number of consumers.
ImageWithName - Datensatzklasse in de.edux.augmentation.io
ImageWithName(BufferedImage, String) - Konstruktor für Datensatzklasse de.edux.augmentation.io.ImageWithName: Erstellt eine Instanz einer Datensatzklasse ImageWithName.
IMatrixArithmetic - Schnittstelle in de.edux.core.math
IMatrixProduct - Schnittstelle in de.edux.core.math: The IMatrixProduct interface defines a method for multiplying two matrices.
IMatrixVectorProduct - Schnittstelle in de.edux.core.math: The IMatrixVectorProduct interface specifies the operation for multiplying a matrix by a vector.
imputation(int, ImputationStrategy) - Methode in Schnittstelle de.edux.data.provider.DataPostProcessor: Performs imputation on missing values in a specified column index using the provided imputation strategy.
imputation(int, ImputationStrategy) - Methode in Klasse de.edux.data.provider.DataProcessor
ImputationStrategy - Enum-Klasse in de.edux.functions.imputation: Enumerates the available imputation strategies for handling missing values in datasets.
IncompatibleDimensionsException - Ausnahmeklasse in de.edux.util.math
IncompatibleDimensionsException(String) - Konstruktor für Ausnahmeklasse de.edux.util.math.IncompatibleDimensionsException
INeuron - Schnittstelle in de.edux.ml.nn.network.api
Initialization - Enum-Klasse in de.edux.functions.initialization: Enumerates strategies for initializing weights in neural network layers, providing methods to apply these strategies to given weight arrays.
inputSize() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente inputSize zurück.
invertMatrix(double[][]) - Methode in Schnittstelle de.edux.util.math.MatrixOperations: Inverts the given matrix and returns the resulting matrix.
IPerceptron - Schnittstelle in de.edux.ml.nn.network.api
ISupportVectorMachine - Schnittstelle in de.edux.ml.svm

K

KnnClassifier - Klasse in de.edux.ml.knn: The KnnClassifier class provides an implementation of the k-Nearest Neighbors algorithm for classification tasks.
KnnClassifier(int) - Konstruktor für Klasse de.edux.ml.knn.KnnClassifier: Initializes a new instance of KnnClassifier with specified k.

L

LabelDimensionConverter - Klasse in de.edux.util
LabelDimensionConverter() - Konstruktor für Klasse de.edux.util.LabelDimensionConverter
labelSamples() - Methode in Datensatzklasse de.edux.ml.randomforest.Sample: Gibt den Wert für die Datensatzkomponente labelSamples zurück.
LEAKY_RELU - Enum-Konstante in Enum-Klasse de.edux.functions.activation.ActivationFunction
learningRate() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente learningRate zurück.
LEFT_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
LINEAR - Enum-Konstante in Enum-Klasse de.edux.ml.svm.SVMKernel
loadDataSetFromCSV(File, char, boolean, int[], int) - Methode in Schnittstelle de.edux.data.provider.Dataloader: Loads a dataset from the specified CSV file, processes it, and returns a DataProcessor that is ready to be used for further operations such as data manipulation or analysis.
loadDataSetFromCSV(File, char, boolean, int[], int) - Methode in Klasse de.edux.data.provider.DataProcessor
loadKernel() - Methode in Schnittstelle de.edux.core.math.matrix.cuda.CUDAKernelUser
loadKernel() - Methode in Klasse de.edux.core.math.matrix.cuda.operations.CudaMatrixProduct
loadKernel() - Methode in Klasse de.edux.core.math.matrix.cuda.operations.CudaMatrixVectorProduct
lossFunction() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente lossFunction zurück.
LossFunction - Enum-Klasse in de.edux.functions.loss

M

MathMatrix - Klasse in de.edux.util.math
MathMatrix() - Konstruktor für Klasse de.edux.util.math.MathMatrix
MatrixArithmetic - Klasse in de.edux.core.math.matrix.parallel
MatrixArithmetic() - Konstruktor für Klasse de.edux.core.math.matrix.parallel.MatrixArithmetic
MatrixOperations - Schnittstelle in de.edux.util.math: Provides the classes necessary for performing matrix operations in machine learning.
MatrixProduct - Klasse in de.edux.core.math.matrix.parallel.operations
MatrixProduct() - Konstruktor für Klasse de.edux.core.math.matrix.parallel.operations.MatrixProduct
MatrixVectorProduct - Klasse in de.edux.core.math.matrix.parallel.operations
MatrixVectorProduct() - Konstruktor für Klasse de.edux.core.math.matrix.parallel.operations.MatrixVectorProduct
MEAN_ABSOLUTE_ERROR - Enum-Konstante in Enum-Klasse de.edux.functions.loss.LossFunction
MEAN_SQUARED_ERROR - Enum-Konstante in Enum-Klasse de.edux.functions.loss.LossFunction
MODE - Enum-Konstante in Enum-Klasse de.edux.functions.imputation.ImputationStrategy: Imputation strategy that replaces missing values with the most frequently occurring value (mode) in the dataset column.
ModeImputation - Klasse in de.edux.functions.imputation: Implements the IImputationStrategy interface to provide a mode value imputation.
ModeImputation() - Konstruktor für Klasse de.edux.functions.imputation.ModeImputation
MonochromeAugmentation - Klasse in de.edux.augmentation.effects: Applies a monochrome filter to the image, converting it to grayscale.
MonochromeAugmentation() - Konstruktor für Klasse de.edux.augmentation.effects.MonochromeAugmentation
MultilayerPerceptron - Klasse in de.edux.ml.nn.network: The MultilayerPerceptron class represents a simple feedforward neural network, which consists of input, hidden, and output layers.
MultilayerPerceptron(NetworkConfiguration, double[][], double[][]) - Konstruktor für Klasse de.edux.ml.nn.network.MultilayerPerceptron
multiply(double[][], double[]) - Methode in Schnittstelle de.edux.core.math.IMatrixVectorProduct: Multiplies a matrix by a vector and returns the result as a new vector.
multiply(double[][], double[]) - Methode in Klasse de.edux.core.math.matrix.cuda.CudaMatrixArithmetic
multiply(double[][], double[]) - Methode in Klasse de.edux.core.math.matrix.cuda.operations.CudaMatrixVectorProduct
multiply(double[][], double[]) - Methode in Klasse de.edux.core.math.matrix.parallel.MatrixArithmetic
multiply(double[][], double[]) - Methode in Klasse de.edux.core.math.matrix.parallel.operations.MatrixVectorProduct
multiply(double[][], double[][]) - Methode in Schnittstelle de.edux.core.math.IMatrixProduct: Multiplies two matrices together and returns the result as a new matrix.
multiply(double[][], double[][]) - Methode in Klasse de.edux.core.math.matrix.cuda.CudaMatrixArithmetic
multiply(double[][], double[][]) - Methode in Klasse de.edux.core.math.matrix.cuda.operations.CudaMatrixProduct
multiply(double[][], double[][]) - Methode in Klasse de.edux.core.math.matrix.parallel.MatrixArithmetic
multiply(double[][], double[][]) - Methode in Klasse de.edux.core.math.matrix.parallel.operations.MatrixProduct
multiplyMatrices(double[][], double[][]) - Methode in Schnittstelle de.edux.util.math.ConcurrentMatrixMultiplication: Multiplies two matrices and returns the resulting matrix.
multiplyMatrices(double[][], double[][]) - Methode in Klasse de.edux.util.math.MathMatrix

N

NetworkConfiguration - Datensatzklasse in de.edux.ml.nn.config
NetworkConfiguration(int, List<Integer>, int, double, int, ActivationFunction, ActivationFunction, LossFunction, Initialization, Initialization) - Konstruktor für Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Erstellt eine Instanz einer Datensatzklasse NetworkConfiguration.
NoiseInjectionAugmentation - Klasse in de.edux.augmentation.effects
NoiseInjectionAugmentation(int) - Konstruktor für Klasse de.edux.augmentation.effects.NoiseInjectionAugmentation
normalize() - Methode in Schnittstelle de.edux.data.provider.DataPostProcessor: Normalizes the dataset.
normalize() - Methode in Klasse de.edux.data.provider.DataProcessor
normalize(List<String[]>) - Methode in Klasse de.edux.data.provider.DataNormalizer
normalize(List<String[]>) - Methode in Schnittstelle de.edux.data.provider.Normalizer
Normalizer - Schnittstelle in de.edux.data.provider

O

outputLayerActivationFunction() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente outputLayerActivationFunction zurück.
outputLayerWeightInitialization() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente outputLayerWeightInitialization zurück.
outputSize() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt den Wert für die Datensatzkomponente outputSize zurück.

P

performImputation(String[]) - Methode in Klasse de.edux.functions.imputation.AverageImputation: Performs average value imputation on the provided dataset column.
performImputation(String[]) - Methode in Schnittstelle de.edux.functions.imputation.IImputationStrategy: Performs imputation on the provided column data array.
performImputation(String[]) - Methode in Klasse de.edux.functions.imputation.ModeImputation: Performs mode value imputation on the provided dataset column.
performListWiseDeletion() - Methode in Schnittstelle de.edux.data.provider.DataPostProcessor: Performs list-wise deletion on the dataset.
performListWiseDeletion() - Methode in Klasse de.edux.data.provider.DataProcessor
Perspective - Enum-Klasse in de.edux.augmentation.effects.geomentry: Defines common perspective transformations that can be applied to images.
PerspectiveTransformationsAugmentation - Klasse in de.edux.augmentation.effects: Applies a perspective transformation to an image using affine transformations.
PerspectiveTransformationsAugmentation(double, double, double, double, double, double) - Konstruktor für Klasse de.edux.augmentation.effects.PerspectiveTransformationsAugmentation: Constructs a PerspectiveTransformationsAugmentation with custom transformation settings.
PerspectiveTransformationsAugmentation(Perspective) - Konstruktor für Klasse de.edux.augmentation.effects.PerspectiveTransformationsAugmentation: Constructs a PerspectiveTransformationsAugmentation with predefined perspective settings.
predict(double[]) - Methode in Schnittstelle de.edux.api.Classifier: Predicts the output for a single set of input values.
predict(double[]) - Methode in Klasse de.edux.ml.decisiontree.DecisionTree
predict(double[]) - Methode in Klasse de.edux.ml.knn.KnnClassifier
predict(double[]) - Methode in Schnittstelle de.edux.ml.nn.network.api.IPerceptron
predict(double[]) - Methode in Klasse de.edux.ml.nn.network.MultilayerPerceptron
predict(double[]) - Methode in Klasse de.edux.ml.randomforest.RandomForest
predict(double[]) - Methode in Schnittstelle de.edux.ml.svm.ISupportVectorMachine
predict(double[]) - Methode in Klasse de.edux.ml.svm.SupportVectorMachine
predict(double[]) - Methode in Klasse de.edux.ml.svm.SVMModel
processImages() - Methode in Klasse de.edux.augmentation.io.ImageProcessingManager

Q

QUALITY - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.ResizeQuality

R

RandomDeleteAugmentation - Klasse in de.edux.augmentation.effects: This class provides an augmentation that randomly deletes a portion of the image.
RandomDeleteAugmentation(int, int, int) - Konstruktor für Klasse de.edux.augmentation.effects.RandomDeleteAugmentation: Constructs a RandomDeleteAugmentation with specified parameters.
RandomForest - Klasse in de.edux.ml.randomforest: RandomForest Classifier RandomForest is an ensemble learning method, which constructs a multitude of decision trees at training time and outputs the class that is the mode of the classes output by individual trees, or a mean prediction of the individual trees (regression).
RandomForest(int, int, int, int, int, int) - Konstruktor für Klasse de.edux.ml.randomforest.RandomForest
readFile(File, char) - Methode in Klasse de.edux.data.reader.CSVIDataReader
readFile(File, char) - Methode in Schnittstelle de.edux.data.reader.IDataReader
readImage(Path) - Statische Methode in Klasse de.edux.augmentation.core.AbstractAugmentation
readImagePathsAsStream(String) - Methode in Klasse de.edux.augmentation.io.AugmentationImageReader: Reads all image file paths from a specified directory and returns them as a stream.
readImagePathsAsStream(String) - Methode in Schnittstelle de.edux.augmentation.io.IAugmentationImageReader
RELU - Enum-Konstante in Enum-Klasse de.edux.functions.activation.ActivationFunction
resize(BufferedImage) - Methode in Klasse de.edux.augmentation.effects.ResizeAugmentation
ResizeAugmentation - Klasse in de.edux.augmentation.effects: Provides functionality to resize images to a specified width and height.
ResizeAugmentation(double) - Konstruktor für Klasse de.edux.augmentation.effects.ResizeAugmentation: Creates a ResizeAugmentation instance with a specified scale factor which ensures that the image maintains its aspect ratio after the transformation.
ResizeAugmentation(double, ResizeQuality) - Konstruktor für Klasse de.edux.augmentation.effects.ResizeAugmentation: Creates a ResizeAugmentation instance with the specified scaleFactor and resizing quality.
ResizeAugmentation(int, int) - Konstruktor für Klasse de.edux.augmentation.effects.ResizeAugmentation: Creates a ResizeAugmentation instance with the specified target width and height.
ResizeAugmentation(int, int, ResizeQuality) - Konstruktor für Klasse de.edux.augmentation.effects.ResizeAugmentation: Creates a ResizeAugmentation instance with the specified target width, height, and resizing quality.
ResizeQuality - Enum-Klasse in de.edux.augmentation.effects
RIGHT_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
run() - Methode in Klasse de.edux.augmentation.io.ImageConsumer
run() - Methode in Klasse de.edux.augmentation.io.ImageProducer: The run method invoked when the thread starts.
run(String, int, String) - Methode in Schnittstelle de.edux.augmentation.core.AugmentationSequence: Executes the augmentation sequence on a set of images in a specified directory.
run(String, int, String) - Methode in Klasse de.edux.augmentation.core.CompositeAugmentationSequence

S

Sample - Datensatzklasse in de.edux.ml.randomforest
Sample(double[][], double[][]) - Konstruktor für Datensatzklasse de.edux.ml.randomforest.Sample: Erstellt eine Instanz einer Datensatzklasse Sample.
shuffle() - Methode in Schnittstelle de.edux.data.provider.DataPostProcessor: Shuffles the dataset randomly.
shuffle() - Methode in Klasse de.edux.data.provider.DataProcessor
SIGMOID - Enum-Konstante in Enum-Klasse de.edux.functions.activation.ActivationFunction
SOFTMAX - Enum-Konstante in Enum-Klasse de.edux.functions.activation.ActivationFunction
split(double) - Methode in Schnittstelle de.edux.data.provider.DataPostProcessor: Splits the dataset into two separate datasets according to the specified split ratio.
split(double) - Methode in Klasse de.edux.data.provider.DataProcessor
SQUARED_HINGE_LOSS - Enum-Konstante in Enum-Klasse de.edux.functions.loss.LossFunction
SQUEEZE_HORIZONTAL - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
SQUEEZE_VERTICAL - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
STRETCH_HORIZONTAL - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
STRETCH_VERTICAL - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
subtractMatrices(double[][], double[][]) - Methode in Schnittstelle de.edux.util.math.MatrixOperations: Subtracts matrix b from matrix a and returns the resulting matrix.
SupportVectorMachine - Klasse in de.edux.ml.svm: The SupportVectorMachine class is an implementation of a Support Vector Machine (SVM) classifier, utilizing the one-vs-one strategy for multi-class classification.
SupportVectorMachine(SVMKernel, double) - Konstruktor für Klasse de.edux.ml.svm.SupportVectorMachine: Constructs a new instance of SupportVectorMachine with a specified kernel and regularization parameter.
SVMKernel - Enum-Klasse in de.edux.ml.svm
SVMModel - Klasse in de.edux.ml.svm
SVMModel(SVMKernel, double) - Konstruktor für Klasse de.edux.ml.svm.SVMModel

T

TANH - Enum-Konstante in Enum-Klasse de.edux.functions.activation.ActivationFunction
testData() - Methode in Datensatzklasse de.edux.ml.nn.network.api.Dataset: Gibt den Wert für die Datensatzkomponente testData zurück.
TOP_LEFT_CORNER_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
TOP_RIGHT_CORNER_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
TOP_TILT - Enum-Konstante in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective
toString() - Methode in Datensatzklasse de.edux.augmentation.io.ImageWithName: Gibt eine Zeichenfolgendarstellung dieser Datensatzklasse zurück.
toString() - Methode in Datensatzklasse de.edux.ml.nn.config.NetworkConfiguration: Gibt eine Zeichenfolgendarstellung dieser Datensatzklasse zurück.
toString() - Methode in Datensatzklasse de.edux.ml.nn.network.api.Dataset: Gibt eine Zeichenfolgendarstellung dieser Datensatzklasse zurück.
toString() - Methode in Datensatzklasse de.edux.ml.randomforest.Sample: Gibt eine Zeichenfolgendarstellung dieser Datensatzklasse zurück.
train(double[][], double[][]) - Methode in Schnittstelle de.edux.api.Classifier: Trains the model using the provided training inputs and targets.
train(double[][], double[][]) - Methode in Klasse de.edux.ml.decisiontree.DecisionTree
train(double[][], double[][]) - Methode in Klasse de.edux.ml.knn.KnnClassifier
train(double[][], double[][]) - Methode in Schnittstelle de.edux.ml.nn.network.api.IPerceptron
train(double[][], double[][]) - Methode in Klasse de.edux.ml.nn.network.MultilayerPerceptron
train(double[][], double[][]) - Methode in Klasse de.edux.ml.randomforest.RandomForest
train(double[][], double[][]) - Methode in Klasse de.edux.ml.svm.SupportVectorMachine
train(double[][], int[]) - Methode in Schnittstelle de.edux.ml.svm.ISupportVectorMachine
train(double[][], int[]) - Methode in Klasse de.edux.ml.svm.SVMModel
trainData() - Methode in Datensatzklasse de.edux.ml.nn.network.api.Dataset: Gibt den Wert für die Datensatzkomponente trainData zurück.
transposeMatrix(double[][]) - Methode in Schnittstelle de.edux.util.math.MatrixOperations: Transposes the given matrix and returns the resulting matrix.

U

updateWeights(double[], double) - Methode in Schnittstelle de.edux.ml.nn.network.api.INeuron

V

valueOf(String) - Statische Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
valueOf(String) - Statische Methode in Enum-Klasse de.edux.augmentation.effects.ResizeQuality: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
valueOf(String) - Statische Methode in Enum-Klasse de.edux.functions.activation.ActivationFunction: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
valueOf(String) - Statische Methode in Enum-Klasse de.edux.functions.imputation.ImputationStrategy: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
valueOf(String) - Statische Methode in Enum-Klasse de.edux.functions.initialization.Initialization: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
valueOf(String) - Statische Methode in Enum-Klasse de.edux.functions.loss.LossFunction: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
valueOf(String) - Statische Methode in Enum-Klasse de.edux.ml.svm.SVMKernel: Gibt die Enum-Konstante dieser Klasse mit dem angegebenen Namen zurück.
values() - Statische Methode in Enum-Klasse de.edux.augmentation.effects.geomentry.Perspective: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.
values() - Statische Methode in Enum-Klasse de.edux.augmentation.effects.ResizeQuality: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.
values() - Statische Methode in Enum-Klasse de.edux.functions.activation.ActivationFunction: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.
values() - Statische Methode in Enum-Klasse de.edux.functions.imputation.ImputationStrategy: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.
values() - Statische Methode in Enum-Klasse de.edux.functions.initialization.Initialization: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.
values() - Statische Methode in Enum-Klasse de.edux.functions.loss.LossFunction: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.
values() - Statische Methode in Enum-Klasse de.edux.ml.svm.SVMKernel: Gibt ein Array mit den Konstanten dieser Enum-Klasse in der Reihenfolge ihrer Deklaration zurück.

W

weightInitialization(int, double[]) - Methode in Enum-Klasse de.edux.functions.initialization.Initialization

X

XAVIER - Enum-Konstante in Enum-Klasse de.edux.functions.initialization.Initialization: Enumerates strategies for initializing weights in neural network layers, providing methods to apply these strategies to given weight arrays.

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