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What is Model Evaluation Techniques in ML about?

Model Evaluation is crucial in determining the best machine learning model and its future performance. It involves assessing the reliability of a model using test datasets and avoiding overfitting by not using training data for evaluation. Key evaluation methods include accuracy, precision, recall, and F1 score, often visualized through a confusion matrix.

Author

l226451

Language

EN