N-Fold Cross-Validation: Revision history

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    4 November 2024

    • curprev 17:0517:05, 4 November 2024‎ 핵톤 talk contribs‎ 5,458 bytes +5,458‎ Created page with "N-Fold Cross-Validation is a technique used in machine learning to evaluate a model's performance by dividing the dataset into multiple subsets, or "folds." In this method, the dataset is split into N equal parts, where the model is trained on N-1 folds and tested on the remaining fold. This process is repeated N times, each time using a different fold as the test set, and the results are averaged to obtain an overall performance estimate. N-fold cross-validation helps t..." Tag: Visual edit
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