Material associated to the publication project on local trees methods for classification

Creating a classification decision tree that predicts heart disease. 79% Recall and 70% Precision

This repo contains an R programming project that implements and compares decision tree models including C5.0, C5.4 and CART.

Build, train and deploy ML model to classify penguin types on tabular data

Predict if the customer will churn or not

Using Logistics, Classification, and KNN modelling to predict if a credit card account will default.

Implementation of a Decision Tree(The ID3 algorithm) using Python3

Focused customer retention programs

ML projects, which I worked on utilising different machine learning algorithms.

Using the tree library to construct a classification tree

Classification of movie rankings

Analyze the ATM dataset and predict the monthly withdrawal and rating of an ATM based on the features in the dataset 🏧

Material for the Computational Statistics Project | Summer 2022 | University of Bonn

My Matlab Ph.D. thesis coding project: the enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) structure-based tool used for classification tasks. The credits: the v.1.0 was developed by Dr. M. Rybnik under supervision of Prof. K. Madani

Class Project for Introduction to Statistical Reasoning and Data Science: Exploratory Statistical Analysis on Royal Canadian Yacht Club Dataset

UNCW BAN 502 This course explores methods for model selection, parameter estimation, and validation. Focused on techniques and algorithms from the statistical and machine learning disciplines.

from Wesleyan University

We predicted whether there is less chance or more chance of heart disease by exploring different Data Mining techniques like logistic regression, classification trees, and neural networks. We employed various algorithms and choose the model which gives the best prediction results by comparing the accuracy measures to avoid overfitting.