Assumptions of Logistic Regression, Clearly Explained

This is a binary classification problem related with Autistic Spectrum Disorder (ASD) screening in Adult individual. Given some attributes of a person, my model can predict whether the person would have a possibility to get ASD using different Supervised Learning Techniques and Multi-Layer Perceptron.

Tools for developing binary logistic regression models

Building a binary classification model to determine whether or not an employee in the tech industry chooses to seek treatment for a mental health condition

Supervised Machine Learning to predict Credit Risk. Review of Logistic Regression and Random Forest Classifier with and without scaling.

Course Machine Learning This project is based on 2 case-studies: Vote Prediction and Text Analysis. The first project is to predict which party a citizen is going to vote for on the basis of their age and according to the answers given by the citizens to the questions asked in a survey conducted. The second project is based on the analysis of th…

Base R Implementation of Logistic Regression from Scratch with Regularization, Laplace Approximation and more

Prediction of loan-applications approval status through machine learning (in SAS).

Projects related to Logistic regression - logit logistic regression - Lead Scoring Case Study

Logistic Regression model to assign probabilities of outcomes for any possible matchup in the 2022 NCAA Men's Basketball Tournament

This repository hosts a logistic regression model for telecom customer churn prediction. Trained on historical data, it analyzes customer attributes like account weeks, contract renewal status, and data plan usage to forecast churn likelihood. Its insights aid telecom companies in proactively retaining customers and mitigating churn rates.