ON-LINE MIXTURE-BASED ALTERNATIVE TO LOGISTIC REGRESSION

Merging Strategy Based on Logistic Regression

With the development of network technology, the users looking for information may send a request to various selected databases and then inspect multiple result lists. To overcome such multiple inspections, the database merging strategy involves the merging of the retrieval results produced by separate, autonomous servers into an effective, single ranked list. To achieve this merging, this study...

Transfer Learning Based on Logistic Regression

In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer learning in remote sensing on the basis of logistic regression. Logistic regression is a discriminative probabilistic classifier of low computational complexity, which can deal w...

Notes on Logistic Regression

Experiments on logistic regression

In this report, several experiments have been conducted on a spam data set with Logistic Regression based on Gradient Descent approach. First, the overfitting effect is shown with basic settings (vanilla version). Then Stochastic Gradient Descent and 2-Norm Regularization techniques are both implemented with demonstration of the benefits of these two methods in preventing overfitting. Besides, ...

Simulation-based Regularized Logistic Regression

In this paper, we develop a simulation-based framework for regularized logistic regression, exploiting two novel results for scale mixtures of normals. By carefully choosing a hierarchical model for the likelihood by one type of mixture, and implementing regularization with another, we obtain new MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the d...