Model Evaluation: Revision history

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    2 December 2024

    • curprev 16:2116:21, 2 December 2024‎ Deposition talk contribs‎ 4,789 bytes +4,789‎ 새 문서: '''Model Evaluation''' refers to the process of assessing the performance of a machine learning model on a given dataset. It is a critical step in machine learning workflows to ensure that the model generalizes well to unseen data and performs as expected for the target application. ==Objectives of Model Evaluation== The key objectives of model evaluation are: *'''Assess Performance:''' Measure how well the model predicts outcomes. *'''Compare Models:''' Evaluate multiple models... Tag: Visual edit
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