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Beschreibung
Abstract class for augmentation operations.
Enumerates common activation functions used in neural networks and similar machine learning
architectures.
Builder class for creating an augmentation sequence.
Implementation of
IAugmentationImageReader to read image paths from a specified
directory.Defines a sequence of image augmentation operations.
Implements the
IImputationStrategy interface to provide an average value imputation.This class provides an augmentation that applies a Gaussian blur to an image.
This augmentation technique adjusts an image's brightness value by a specified amount
Provides a common interface for machine learning classifiers within the Edux API.
This class implements an augmentation that applies color equalization to an image.
Composite augmentation that applies a sequence of augmentations.
This class enhances the contrast of an image.
This class provides an augmentation that crops an image based on a specified factor.
The
Dataloader interface defines a method for loading datasets from CSV files.The
DataPostProcessor interface defines a set of methods for post-processing data.A Decision Tree classifier for predictive modeling.
Applies an elastic transformation to an image, simulating natural distortions.
This class provides an augmentation that randomly flips an image either horizontally or
vertically.
Defines a strategy interface for imputing missing values within a column of data.
Handles the production of images from a specified directory, queuing them for further processing.
The IMatrixProduct interface defines a method for multiplying two matrices.
The IMatrixVectorProduct interface specifies the operation for multiplying a matrix by a vector.
Enumerates the available imputation strategies for handling missing values in datasets.
Enumerates strategies for initializing weights in neural network layers, providing methods to
apply these strategies to given weight arrays.
The
KnnClassifier class provides an implementation of the k-Nearest Neighbors algorithm
for classification tasks.Provides the classes necessary for performing matrix operations in machine learning.
Implements the
IImputationStrategy interface to provide a mode value imputation.Applies a monochrome filter to the image, converting it to grayscale.
The
MultilayerPerceptron class represents a simple feedforward neural network, which
consists of input, hidden, and output layers.Defines common perspective transformations that can be applied to images.
Applies a perspective transformation to an image using affine transformations.
This class provides an augmentation that randomly deletes a portion of the image.
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).
Provides functionality to resize images to a specified width and height.
The
SupportVectorMachine class is an implementation of a Support Vector Machine (SVM)
classifier, utilizing the one-vs-one strategy for multi-class classification.