Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

CApriori	Class to perform frequent itemset mining using the Apriori algorithm
CConnection	Represents a connection between neurons with a weight and a change in weight
CDecisionTreeClassifier	Implements a Decision Tree Classifier
CDecisionTreeRegressor	Implements a Decision Tree Regressor
CEclat	Class to perform frequent itemset mining using the Eclat algorithm
CHierarchicalClustering	Agglomerative Hierarchical Clustering for clustering tasks
CKMeans	Implements the K-Means clustering algorithm with K-Means++ initialization
CKNNClassifier	K-Nearest Neighbors Classifier for classification tasks
CKNNRegressor	K-Nearest Neighbors Regressor for regression tasks
CLogisticRegression	Logistic Regression model for binary classification tasks
CMultilinearRegression	A class that implements Multilinear Regression for predicting values based on multiple features
CNeuralNetwork	Represents the neural network consisting of layers of neurons
CNeuron	Represents a single neuron in the neural network
CPolynomialRegression	Polynomial Regression model for fitting polynomial curves
CRandomForestClassifier	Implements a Random Forest Classifier
CRandomForestRegressor	Implements a Random Forest Regressor
CSupportVectorRegression	Support Vector Regression using the ε-insensitive loss function