c++ incremental 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.

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

Decision tree regression implementation by MATLAB.

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

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.

Loan Approval Predictor using python

Visualization of C4.5 Algorithm

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

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%

Membuat klasifikasi penyakit daun teh menggunakan algoritma C45/Decision Tree

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

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