Precision
- Measures correctness among predicted positives.
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Scikit-learn
- Provides ready-made algorithms and metrics.
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Recall
- Measures how many actual positives are caught.
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NumPy
- Handles arrays and matrix operations.
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F1 Score
- Single metric combining both to compare models.
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pandas
- Helps prepare and analyze structured datasets.
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Confusion Matrix
- Table that shows where predictions were right or wrong.
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Matplotlib
- Draws charts and graphs for analysis.
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ROC Curve
- Plots true-positive vs false-positive rates.
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