February 2019
Beginner to intermediate
382 pages
10h 1m
English
When selecting the best combination of feature and value as the splitting point, two criteria such as Gini Impurity and Information Gain can be used to measure the quality of separation.
Gini Impurity, as its name implies, measures the impurity rate of the class distribution of data points, or the class mixture rate. For a dataset with K classes, suppose data from class
take up a fraction
of the entire dataset, the Gini Impurity of this dataset is written as follows:
Lower Gini Impurity indicates a purer ...