Threshold Tuning: Difference between revisions
Thakshashila (talk | contribs) Created page with "= Threshold Tuning = '''Threshold Tuning''' is the process of selecting the best decision threshold in a classification model to optimize performance metrics such as Precision, Recall, F1 Score, or Accuracy. It is crucial in models that output '''probabilities''' rather than direct class labels. == Why Threshold Tuning Matters == Many classifiers (e.g., Logistic Regression, Neural Networks) output a probability score indicating how likely an instance b..." |
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threshold tuning in machine learning, decision threshold optimization, best classification threshold, tuning classifier threshold, precision recall tradeoff, threshold selection, binary classification threshold | threshold tuning in machine learning, decision threshold optimization, best classification threshold, tuning classifier threshold, precision recall tradeoff, threshold selection, binary classification threshold | ||
[[Category:Artificial Intelligence]] | |||