Cross-Validation: Revision history

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    5 November 2024

    • curprev 02:2802:28, 5 November 2024‎ 핵톤 talk contribs‎ 4,467 bytes +4,467‎ Created page with "Cross-Validation is a technique in machine learning used to evaluate a model’s performance on unseen data. It involves partitioning the dataset into multiple subsets, training the model on some subsets while testing on others. Cross-validation helps detect overfitting and underfitting, ensuring the model generalizes well to new data. ==Key Concepts in Cross-Validation== Cross-validation is based on the following key principles: *'''Training and Validation Splits''': Cr..." Tag: Visual edit
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