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@ -137,22 +137,24 @@ The result will be the model's predictions for the entire dataset.
2. Bernoulli Naive Bayes 2. Bernoulli Naive Bayes
3. Gaussian Naive Bayes 3. Gaussian Naive Bayes
8. ***Support Vector Classification*** 8. ***Support Vector Classification***
9. ***K-Means*** 1. Primal Formulation (Hinge Loss Objective)
10. ***k-Nearest Neighbors*** 2. Dual Formulation (Via Lagrangian Multipliers)
11. ***Outlier Finder (Using z-scores)*** 10. ***K-Means***
12. ***Matrix Decompositions*** 11. ***k-Nearest Neighbors***
12. ***Outlier Finder (Using z-scores)***
13. ***Matrix Decompositions***
1. SVD Decomposition 1. SVD Decomposition
2. Cholesky Decomposition 2. Cholesky Decomposition
- Positive Definiteness Checker - Positive Definiteness Checker
3. QR Decomposition 3. QR Decomposition
13. ***Numerical Analysis*** 14. ***Numerical Analysis***
14. ***Linear Algebra Module*** 15. ***Linear Algebra Module***
15. ***Statistics Module*** 16. ***Statistics Module***
16. ***Data Processing Module*** 17. ***Data Processing Module***
1. Setting and Printing Datasets 1. Setting and Printing Datasets
2. Feature Scaling 2. Feature Scaling
3. Mean Normalization 3. Mean Normalization
4. One Hot Representation S
5. Reverse One Hot Representation 5. Reverse One Hot Representation
17. ***Utilities*** 17. ***Utilities***
1. TP, FP, TN, FN function 1. TP, FP, TN, FN function