This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.

Several ML Algorithms implemented from scratch, without using inbuilt libraries. Regression Models, GDA, SVM, Naive Bayes, Decision Tree, PCA using SVD, Neural Network

Detects false banknotes in the UC Irvine dataset.

MATLAB implementation of a decision tree based on ID3 capable of binary classification and handling of continuous features

Heart-Disease dataset analysis using Matlab and the Orange framework.

Machine learning homework solutions

Implementation of decision tree from the scratch using entropy as criteria for information gain calculations.

Boiled egg problems (Solve with LDA, QDA, Naive Bayes Classifiers, decision tree, pruned decision tree)

基于SparseEA的特征选择方法在毒性分类中的应用