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@ -135,18 +135,23 @@ The result will be the model's predictions for the entire dataset.
2. Bernoulli Naive Bayes
3. Gaussian Naive Bayes
8. ***Support Vector Classification***
8. ***K-Means***
9. ***k-Nearest Neighbors***
10. ***Outlier Finder (Using z-scores)***
11. ***Linear Algebra Module***
12. ***Statistics Module***
13. ***Data Processing Module***
9. ***K-Means***
10. ***k-Nearest Neighbors***
11. ***Outlier Finder (Using z-scores)***
12. ***Matrix Decompositions***
1. SVD Decomposition
2. Cholesky Decomposition
- Positive Semidefiniteness Checker
3. QR Decomposition
13. ***Linear Algebra Module***
14. ***Statistics Module***
15. ***Data Processing Module***
1. Setting and Printing Datasets
2. Feature Scaling
3. Mean Normalization
4. One Hot Representation
5. Reverse One Hot Representation
14. ***Utilities***
16. ***Utilities***
1. TP, FP, TN, FN function
2. Precision
3. Recall