Measures Seven popular ML models (Random Forest, Decision Tree, Logistic ... and multinomial deviance loss functions, with a learning rate of 0.1 and 100 boosting stages. All these algorithms were ...

Multinomial Naïve Bayes is a good match for our data for several reasons: There are several other machine learning models including logistic regression, support vector machines, random forests ...

Multinomial logistic regression achieved 81.2% accuracy in predicting reporting tendencies based on event significance and source characteristics. Bayesian inference highlighted significant tendencies ...

This project demonstrates how to implement simple linear regression from scratch using Python, without relying on libraries like Scikit-Learn. The implementation includes data preprocessing, model ...

The system uses logistic regression to analyze various health indicators and classify patients as either having heart disease or being healthy.