Getting Started with Scikit‐learn

The easiest way to get started with machine learning with Scikit‐learn is to start with linear regression. Linear regression is a linear approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables). For example, imagine that you have a set of data comprising the heights (in meters) of a group of people and their corresponding weights (in kg):

%matplotlib inline
import matplotlib.pyplot as plt
 
# represents the heights of a group of people in meters
heights = [[1.6], [1.65], [1.7], [1.73], [1.8]]
 
# represents the weights of a group of people in kgs
weights = [[60], [65], [72.3], [75], [80]]
 
plt.title('Weights plotted against heights')
plt.xlabel('Heights in meters')
plt.ylabel('Weights in kilograms')
 
plt.plot(heights, weights, 'k.')
 
# axis range for x and y
plt.axis([1.5, 1.85, 50, 90])
plt.grid(True) 

When you...