This project applies classification techniques to predict rock categories using 11 features. It involves data preprocessing, splitting into training, validation, and testing subsets, and exploring ...

This book also explains the differences and similarities between the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of ...

Sparse Multinomial Logistic Regression (SMLR) is widely used in the field of image classification, multi-class object recognition, and so on, because it has the function of embedding feature selection ...

[3] Log-Linear Bayesian Additive Regression Trees for Multinomial Logistic and Count Regression Models. Journal of the American Statistical Association (2021).

Bivariable multilevel multinomial logistic regression analysis employed to identify variables eligible for the multivariable analysis. Variables with a p value less than 0.20 in this analysis and ...

I have used Multinomial Naive Bayes, Random Trees Embedding, Random Forest Regressor, Random Forest Classifier, Multinomial Logistic Regression, Linear Support Vector Classifier, Linear Regression, ...