Information Gain: Revision history

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4 November 2024

  • curprev 16:0616:06, 4 November 2024‎ 핵톤 talk contribs‎ 4,722 bytes +4,722‎ Created page with "Information Gain is a metric used in machine learning to measure the effectiveness of a feature in classifying data. It quantifies the reduction in entropy (impurity) achieved by splitting a dataset based on a particular feature. Information gain is widely used in decision tree algorithms to select the best feature for each node split, maximizing the model’s predictive accuracy. ==Definition of Information Gain== Information gain is defined as the difference in entropy..." Tag: Visual edit
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