Gini Impurity (Data Science): 편집 역사

2024년 11월 4일 (월)

• 최신이전 11:512024년 11월 4일 (월) 11:51‎ 핵톤 토론 기여‎ 2,355 바이트 +2,355‎ Created page with "'''Gini Impurity''' is a metric used in data science, particularly in decision tree algorithms, to measure the "impurity" or diversity of a dataset. It helps in determining how well a split at a node separates the data into distinct classes, making it essential for classification problems. ==Definition== Gini impurity calculates the probability that a randomly chosen element from a dataset will be incorrectly classified if it is randomly labeled accordi..." 태그: 시각 편집