Linear regression is one of the most popular algorithms to predict the numeric outcome based on observed features. The default implementation in R for the linear regression is the lm() function. For a larger dataset with a large number of variables, this could take a very long time to run. The rxFastLinear() function for the RevoScaleR library offers a very fast implementation of linear regression with a larger dataset with many variables. In this recipe, you will build a linear regression model to predict arrival delay time as a function of the origin and destination airport along with the departure delay and the day of the week.
Linear regression with larger data (rxFastLiner)
Getting ready
To build a linear regression model...