Lasso Regression : Linear Model: Lasso Regression, also known as Least Squares Regression, is a linear regression method focused on minimizing the total squared difference between predicted and actual values in a dataset. Sparsity: Lasso can set some coefficients to exactly zero, which promotes sparsity. In the process of simplifying the model and removing superfluous …
Lasso Regression in Machine Learning with Python Read More »
Ridge Regression : Ridge Regression is used for regression tasks, particularly deal with linear regression. It deals with datasets that exhibit multicollinearity among the independent variables which can result in erratic regression coefficient estimations, which can cause overfitting and subpar generalization. To fight overfitting, Ridge Regression adds a twist to the usual linear regression recipe. …
Ridge Regression in Machine Learning with Python Read More »
QDA – Quadratic Discriminant Analysis It applies to classification problems in supervised machine It calculates the likelihood that a data point belongs to each class using the Bayes theorem. Its goal is to simulate each class’s predictor distribution independently. How it’s different from LDA? Linear Discriminant Analysis (LDA) and QDA are similar. Both employed in …
Quadratic Discriminant Analysis in Machine Learning with Python Read More »