Decision tree is a supervised machine learning algorithm that is used for both classification and regression tasks. It works by recursively partitioning the feature space into smaller and smaller sub-spaces based on the values of the input features until it reaches a stopping criterion. Here is a step-by-step explanation of…

Support Vector Machine (SVM) is a popular supervised machine learning algorithm used for classification and regression analysis. SVM works by finding the optimal decision boundary or hyperplane that separates different classes in a given dataset. …

R-squared (R2) is a statistical measure that represents the proportion of variation in the dependent variable that is explained by the independent variables in a regression model. …

Gradient descent is an optimization algorithm used to minimize a cost function in machine learning. It works by iteratively adjusting the parameters of the model in the direction of the steepest decrease in the cost function. Mathematically, gradient descent can be explained as follows: Let’s say we have a cost…