To predict which customer is most likely to convert

This project demonstrates how to build a logistic regression model and understanding the evaluation metrics to determine if the model is performing well or not

This Prediction is a research analysis process on data using classification algorithms to compare the accuracy rate for each algorithm given below on this Monkey Pox data such as ( K-Neighbors Classifier, RandomForest Classifier, AdaBoost Classifier, Bagging Classifier, Gradient Boosting Classifier, Decision Tree Classifier )

ROC visualization tool for multi-class data

ML project focused on predicting Titanic passenger survival using various algorithms and extensive data analysis techniques. This project includes detailed data visualization and interpretation to uncover key factors affecting survival. By leveraging various ML models the analysis aims to achieve high predictive accuracy.

Detecting credit card fraud detection. Selecting an optimum threshold with analysis of confusion matrix and ROC curce

Prediction of hospital length of stay at time of admission using support vector classifier

Credit Card Fraud Detection algorithm using smote , confusion matrix, correlation matrix, density plots and ROC-AUC curve . Model - Logistic Regression, Knn, Isolation Forest

This project aims to create a classifier that can predict whether or not a candidate will change their job by using historical data on candidate demographics and details about their education and experience using different classification machine learning models.

Analyse the factors that lead to employee attrition at IBM.

Сегментация КТ-снимков лёгких для выявления поражения тканей от COVID-19 на основе глубоких свёрточных нейронных сетей

What makes fine wine? The main goal of this investigation is to examine which physicochemical features of wine provide the most information about its quality.

Fundamental ML Algorithms in Python

Shiny app for generation of ROC curves

Maximizing Bank's Profitability

Projet de modélisation supervisée - SCORING

Wolfram Language (aka Mathematica) paclet for Receiver Operation Characteristic (ROC) functions.

Predict and prevent customer churn in the telecom industry with this project. Harness the power of advanced analytics and Machine Learning on a diverse dataset to develop a robust classification model. Gain deep insights into customer behavior and identify critical factors influencing churn using interactive Power BI visualizations.

Hormone Therapy Decision Support System for Breast Cancer