Videos tagged with Regression

We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thresholds. Using such a model, we could theoretically and algorithmically reduce ordinal regression problems to binary classification problems in the area of ensemble learning. Based on the reduction, we derive novel large-margin bo...

In this paper we explore the use of Tree Augmented Naive Bayes (TAN) in regression problems where some of the independent variables are continuous and some others are discrete. The proposed solution is based on the approximation of the joint distribution by a Mixture of Truncated Exponentials (MTE). The construction of the TAN structure requires the use of the conditional mutual information, wh...

Multiplicative update rules have proven useful in many areas of machine learning. Simple to implement, guaranteed to converge, they account in part for the widespread popularity of algorithms such as nonnegative matrix factorization and Expectation-Maximization. In this paper, we show how to derive multiplicative updates for problems in L1-regularized linear and logistic regression. For L1&ndas...