Regression Splines in R and Python

The linear model is named so because of the linear relationship between the input (independent variable) and the output (dependent variable). Even though we know it's of a high probability that the real-world data shows nonlinearity, people usually keep regarding the linear model as one of the top choices. The reasons for that are mainly two things. First, with acceptable approximation, the linear model is one of the simplest models to interpret. Second, the low complexity of the linear model makes it very unlikely to overfit the data, especially when you have small n (sample size) and large p ( variable number).