Table of Contents Model Validation Model Validation Model validation is the process of evaluating a machine learning model’s performance on data it hasn’t seen during training. The goal is to ensure that the model generalizes well to new, unseen data Data Splitting Data set typically split into three sets Training Set Validation Set […]
Table of Contents Measure of Model Performance Distance Matrix and Confusion matrix are two measures of Model performance Distance Matrix A distance matrix is a square matrix that contains the distances between each pair of points in a dataset. It is used in machine learning for below models Clustering Algorithms: Algorithms like K-Means use
Table of Contents Kernel Methods Kernel methods are a class of algorithms used for pattern analysis, where the data is transformed into a higher-dimensional space to make it easier to classify or analyze. The kernel trick is particularly useful for algorithms that rely on dot products (e.g., Support Vector Machines), allowing them to operate in
Table of Contents Support Vector Machine Classification Classification is a fundamental task in machine learning where the goal is to assign new input data to one of several predefined categories or classes. It’s a form of supervised learning, meaning that the model is trained on a labeled dataset where the correct output (class) is known.