

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()

3 Linear Methods for Regression

3.1 Introduction

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.

3 Linear Methods for Regression

3.1 Introduction

3.2 Linear Regression Models and Least Squares