```
In [1]:
```# %load ../../preconfig.py
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
plt.rcParams['axes.grid'] = False
#import numpy as np
#import pandas as pd
#import sklearn
#import itertools
import logging
logger = logging.getLogger()

For prediction purposes linear methods can sometimes outperform fancier nonlinear models, especially in situations with small numbers of training cases, low signal-to-noise ratio or sparse data.

linear methods $\to$ basis-function methods.

an understanding of linear methods is essential for understanding nonlinear ones.