Implementations of a few regressors and classifiers using only numpy for my course
Implemented
- Ridge Regressor: Linear Regression with ridge regularization (l2 regularization)
- Batch Gradient Descent Linear Regression
- Stochastic Gradient Descent
- Lasso Regression, with Feature Selection (l1 regularization)
- Naive Bayes Classification, using a Gaussian Distribution
- Logistic Regression using stochastic gradient descent
- Neural Network with a single hidden layer and a sigmoid transfer
- K-fold Cross Validation for hyperparameter tuning
- Kernel Logistic Regression using both linear and Hamming distance kernels