Preddiction models based on binary classification

Developed logistic regression and XgBoost for binary classification problem for Titanic Data set

Project Descriptioin

A basic binary classification model and an advanced classification model is used for the prediction of and their accuracy and performance is measured at the end.

Source of the data - https://www.kaggle.com/competitions/titanic/data
First basic model with logistic regression
second model is based on XgBoost
An interactive web app implemented with streamlit to deploy the model locally

Usage

Collaborators

We would like to acknowledge the following individuals for their contributions to this project

About

ReDI project collaboration

Languages

Language:Python 88.6%Language:Cython 4.5%Language:C++ 4.4%Language:Jupyter Notebook 1.3%Language:C 0.9%Language:JavaScript 0.2%Language:Fortran 0.1%Language:PowerShell 0.0%Language:Smarty 0.0%Language:CSS 0.0%Language:Forth 0.0%Language:R 0.0%Language:HTML 0.0%Language:Batchfile 0.0%Language:Jinja 0.0%Language:XSLT 0.0%Language:CMake 0.0%

thisalmadu / ReDI