Abstract
There are various regression algorithms developed to predict either numerical values or categorical variables. Linear regression algorithms deal with predicting numeric values and are one of the simplest, yet most common algorithms used for predicting numeric values. They attempt to find the equation of a line that best fits the trend of the data set. Linear regression algorithms were extended to logistic regressions that deal with classifying data points. In this chapter, we learn about linear and logistic regression algorithms and implement our knowledge for hands-on experiences in R.
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