If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can use R-style formulas. First, you need to import statsmodels and its ...

Abstract: We investigate sequential nonlinear regression and introduce a novel gradient boosting algorithm that exploits the residuals, i.e., prediction errors, as additional features, as inspired by ...

Abstract: In this article, we extend the popular supervised learning technique radial basis function network (RBFN) for regression modeling based on fuzzy responses ...

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 the kernel matrix inverse (Cholesky ...

You don’t like it. You might even reject it. But touchdown scoring explains a lot of what we’ll call variance — luck, to use a crasser term — in fantasy football. That touchdown scoring is inherently ...

ABSTRACT: As extremely important methods, Lp regression methods have attracted the attention of either theoretical or empirical researchers all over the world. As special cases of that, quantile and ...

Department of Chemical Engineering, University of Louisiana, Lafayette, Louisiana 70504, United States Energy Institute of Louisiana, University of Louisiana, Lafayette, Louisiana 70504, United States ...

Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, ...