Logistic Regression

Predicting Likelihood for Loan Default Among Loan App Borrowers: A logit Classification Approach

Predicting the likelihood of missed loan repayments is essential for banks and credit providers to effectively manage lending risks and promote responsible financial services. This research utilises a binary classification approach, specifically logistic regression, to

By admin, 22 May, 2025

Predictors of Radiotherapy Outcomes in Breast Cancer Patients: A Logistic Regression Analysis of Clinical and Dosimetric parameters

This study aimed to predict radiotherapy outcome for breast cancer patients using clinical and dosimetric parameters through logistic regression analysis. The study made use of One Thousand, Four Hundred and Twenty-Two (1422) patients treated for breast cancer at the NSIA Cancer Centre, Lagos University Teaching Hospital (LUTH), Lagos State. Multivariate logistic regression analysis is performed in R Studio, with the level of significance set at p<0.05.

Cyberbullying Detection Using K-Nearest Neighbour and Logistic Regression

Cyberbullying, also known as online bullying is a type of bullying involving the use of digital technologies such as social media, messaging platforms, or other channels available. It is a harmful behavior in online spaces that poses significant challenges to individuals and society. The harmful effect of cyberbullying makes the victims to suffer depression, ill-health, emotional disorder, low self-esteem, physical violence and possibly commit suicide.

Logistic Regression