classification Archives

Introduction to Decision Trees

Decision trees are one of the most powerful and widely used supervised models that can either perform regression or classification. In this tutorial, we’ll concentrate only on the classification setting. A decision tree consists of rules […]

KNN from Scratch

The K-Nearest Neighbor(KNN) classifier is one of the easiest classification methods to understand and is one of the most basic classification models available. KNN is a non-parametric method which classifies based on the distance to the […]

Introduction to Logistic Regression

In this article, we’ll discuss a supervised machine learning algorithm logistic regression. Logistic regression is a probabilistic classifier. It outputs the probability of a point belonging to a specific class. The output lies between [0,1]. Logistic […]

Introduction to K-Nearest Neighbors

The K-nearest neighbor(K-NN) classifier is one of the easiest classification methods to understand and is one of the most basic classification models available. K-NN is a non-parametric method which classifies based on the distance to the […]

Introduction to Support Vector Machine(SVM)

INTRODUCTION: Support Vector Machine(SVM) is the most popular and powerful supervised machine learning algorithm which is used for both classification and regression. However, it is more popular and extensively used in addressing the classification problems of […]

Performance Measure for Classification(Part-2)

INTRODUCTION: In the last part, we see what a confusion matrix is and some other metrics like TPR, TNR, FPR, and FNR, which are based on the confusion matrix. In this post, we will see about […]

Performance Measures for Classification

Why do we need performance measures? Why do we need performance measures at all? After we developed our classification model, we need to asses the performance of the model. Obviously, we can use accuracy as a […]