Top 6 Regression Algorithms Used In Data Mining And Their Applications In Industry

This supervised machine learning algorithm has strong regularization and can be leveraged both for classification or regression challenges. They are characterized by usage of kernels, the sparseness of the solution and the capacity control gained by acting on the margin, or on number of support vectors, etc. The capacity of the system is controlled by parameters that do not depend on the dimensionality of feature space. Since the SVM algorithm operates natively on numeric attributes, it uses a z-score normalization on numeric attributes. In regression, Support Vector Machines algorithms use epsilon-insensitivity (margin of tolerance) loss function to solve regression problems.