Add all required theoretical and mathematical descriptions of each algorithm implemented. - Linear: - [ ] Lasso Regression - [ ] Linear Regression - [ ] Linear discriminant analysis - [ ] Logistic Regression - [ ] Lowess Regression - [ ] Principal Component Analysis - [ ] Ridge Regression - [ ] Support Vector Machine - [ ] Elastic Net - Tree: - [ ] Decision Tree - [ ] Random Forest - [ ] XGBoost - Probabilistic: - [ ] Bayesian Regression - [ ] Naive Bayes - [ ] Gaussian Mixture Model - [ ] Hidden Markov Model - [ ] Markov's Chain - Clustering: - [ ] DBSCAN - [ ] K-Means - Non-Linear: - [ ] Genetic Algorithm - [ ] K Nearest Neighbors - [ ] Multilayer Perceptron - [ ] Neural Network
Add all required theoretical and mathematical descriptions of each algorithm implemented.
Linear:
Tree:
Probabilistic:
Clustering:
Non-Linear: