Simulations for the paper "Inter node Hellinger Distance based Decision Tree by Pritom Saha Akash, Md. Eusha Kadir, Amin Ahsan Ali, Mohammad Shoyaib"

Implementation of Dynamic Programming Decision Tree algorithm (Kohler et. al. 2024).

The focus is on predicting the quality of wine based on its chemical characteristics. The dataset encompasses diverse chemical attributes, including density and acidity, which serve as the features for three distinct classifier models.

Book Recommender System - 5 approaches

A Performance Study of Naive Bayes Classifier in Advertisement Analysis

This project aims to predict the compressive strength of concrete using various machine learning models. The analysis is performed on a dataset that includes features such as the composition and age of the concrete. The goal is to identify the most effective model for predicting concrete strength.

The project focuses on predicting the presence of heart disease based on various medical variables such as age, sex, and cholesterol level. Decision tree models are employed for this classification task, exploring both basic and hyperparameter-tuned versions.

Python package for strings binary classification, based on trees and regular expressions

Fraud Detection machine learning model utilizes the "DecisionTreeClassifier" to identify fraudulent activities on an online payment app.

Ce TP vise à : - La prise en main de la bibliothèque scikit-learn de Python, dédiée à l'apprentissage automatique - Sensibilisation à l'évaluation des modèles appris en classification supervisée. Iris is a dataset introduced in 1936 by Ronald Aylmer Fisher as an example of discriminant analysis.   This set contains 150 examples of criteria obser…

Data Science Project - Full Depth analysis AND Prediction Using Decision Tree and Random Forest

Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.

Students' Performance Evaluation using Feature Engineering, Feature Extraction, Manipulation of Data, Data Analysis, Data Visualization and at last applying Classification Algorithms from Machine Learning to Separate Students with different grades

Credit Card Fraud Detection System built using Python. The system utilizes machine learning algorithms to detect fraudulent transactions from a given dataset.

Data Science project using decision tree classifier

Using Exploratory Data Analysis(EDA) and building different Machine Learning Models(Logistic Regression, Decision Tree, Random Forest and XGBoost) We'll help Salifort Motors to predict employee turnover rate and retain their talents.

This contains all the project in which i have used Decision Trees and Random Forest to Predict output

This Project aims to predict the prices of Houses using ML classification algorithms and based on that classify whether the house is "Expensive" or "Not Expensive"

Predicting which customers are at high risk of leaving your company or canceling a subscription to a service, based on their behavior with your product.

This data set is a repository of all the houses that were sold in the Ames region in the USA. It has roughly 80 useful features describing the houses’ size, location, and various amenities offered.