Читать книгу Data Science For Dummies - Lillian Pierson - Страница 67

Many statistical and machine learning methods assume that your features are independent. To test whether they’re independent, though, you need to evaluate their correlation — the extent to which variables demonstrate interdependency. In this section, you get a brief introduction to Pearson correlation and Spearman’s rank correlation.

Correlation is quantified per the value of a variable called r, which ranges between –1 and 1. The closer the r-value is to 1 or –1, the more correlation there is between two variables. If two variables have an r-value that’s close to 0, it could indicate that they’re independent variables.