This paper addresses the problem of two-way sparse reduced-rank regression (TSRRR), which aims to estimate a coefficient matrix that is both low-rank and two-way sparse (sparse in both rows and ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

To overcome these issues a hybrid model of eXtreme Gradient Boosting and Logistic Regression (XGBoost-LR) has proposed, which involves with preprocessing of Synthetic Minority Oversampling Technique ...