R: Mining Spatial, Text, Web, and Social Media Data

Penalized regression

The problem of maximum likelihood estimation comes into picture when we include large number of predictors or highly correlated predictors or both in a regression model and its failure to provide higher accuracy in regression problems gives rise to the introduction of penalized regression in data mining. The properties of maximum likelihood cannot be satisfying the regression procedure because of high variability and improper interpretation. To address the issue, most relevant subset selection came into picture. However, the subset selection procedure has some demerits. To again solve the problem, a new method can be introduced, which is popularly known as penalized maximum likelihood estimation method. There are two different ...