This practice project explores Multinomial Logistic Regression for multiclass classification while trying to address severe class imbalance. The goal is to evaluate different techniques, like class ...

Abstract: Big data and data analysis are very necessary and play important role in the operation of organizations especially the future forecasting. To improve the predictive accuracy, an imbalanced ...

Abstract: In this paper, we present multinomial latent logistic regression (MLLR), a new learning paradigm that introduces latent variables to logistic regression. By inheriting the advantages of ...

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

ABSTRACT: Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...