Gini Impurity (Data Science): Revision history

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    3 November 2024

    • curprev 21:5121:51, 3 November 2024‎ 핵톤 talk contribs‎ 2,355 bytes +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..." Tag: Visual edit
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