Survey on Discriminative Least Squares Regression and its Application

This paper presents a short survey of a framework of discriminative method of least squares regression (LSR) model and additionally its applications for. The core plan is to review the Discriminative method of least squares Regression framework and its application areas, wherever it provides the optimum answer. As per we have a tendency to study for applying in varied drawback of classification several new concepts are added to that like μ-dragging that is introduced to force the regression targets of various categories moving on opposite directions specified the distances between categories are often enlarged. Then, the μ-dragging are integrated into the LSR model for multiclass classification. during this means the new learning framework, cited as discriminative method of least squares regression, has a compact model form, wherever there\’s no ought to train two-class machines that are independent of every alternative. With its compact form, this model are often naturally extended for feature selection. So, the aim of this paper is to present survey on Discriminative least squares Regression method for finding its uses in varied fields wherever it may be used for different fine works.