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ML | DA Practice Questions

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What is Error Analysis?

(i) The process of analyzing the performance of a model through metrics such as precision, recall or F1-score.

(ii) The process of scanning mis-classified examples to identify weaknesses of a model.

(iii) The process of tuning hyperparameters to reduce the loss function during training.

(iv) The process of identifying which parts of your model contributed to the error.
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(ii) The process of scanning mis-classified examples to identify weaknesses of a model.

Error analysis involves examining the mistakes made by a machine learning model to gain insights into its weaknesses and areas for improvement. This process involves examining misclassified examples and understanding why the model made incorrect predictions

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