myID3 and myC45 modules implementation (Tubes1B), myMLP module implementation with mini-batch gradient descent (Tubes1C) and 10-fold cross validation scheme implementation (Tubes1D)

Decision tree regression implementation by MATLAB.

A 3-level decision tree achieves a 76.48% success rate in the SUSY file test (https://archive.ics.uci.edu/ml/datasets/SUSY)

Using the decision tree technique based on entropy calculation, this application calculates the hit rate of the HASTIE file with a hit rate higher than 99%

Data Mining project to implement Quinlan's C4.5 decision tree algorithm from scratch for medical data mining using the Thyroid allbp dataset

c++ incremental decision tree

BBM465*ASG4 - In this experiment, we did visual analysis using image files consisting of screenshots. With the threat intelligence module we produced for anti-phishing, we completed website brand classification with screenshots of phishing websites.

Visualization of C4.5 Algorithm

Membuat klasifikasi penyakit daun teh menggunakan algoritma C45/Decision Tree

Repository tugas UAS mata kuliah Kecerdasan Buatan. Tugas yang dikerjakan yaitu membuat sistem pendukung keputusan untuk penentuan ciri ubi jalar dengan metode decision tree algoritma C4.5.

DecisionTreeC45 is a library for creating decision trees using the C4.5 algorithm.

Simple implementation of the ID3 + C4.5 algorithm for decision tree learning

Sistem Pendukung Keputusan untuk menentukan layak dan tidaknya seseorang mendapatkan bantuan PKH dengan menggunakan machine learning yaitu C4.5 dan K-Means

Loan Approval Predictor using python

C4.5 atm data mining

KLASIFIKASI DATA PENYAKIT DIABETES MENGGUNAKAN ALGORITMA DECISION TREE DAN PARTICLE SWARM OPTIMIZATION