Underfitting: Revision history

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    5 November 2024

    • curprev 02:2602:26, 5 November 2024‎ 핵톤 talk contribs‎ 4,364 bytes +4,364‎ Created page with "Underfitting is a common issue in machine learning where a model is too simple to capture the underlying patterns in the data. As a result, the model performs poorly on both training and test datasets, failing to achieve high accuracy. Underfitting occurs when the model lacks the capacity or complexity needed to represent the relationships within the data. ==Causes of Underfitting== Several factors contribute to underfitting in machine learning models: *'''Over-Simplifie..." Tag: Visual edit
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