Tag: Support vector machines
Support Vector Machine algorithm for Machine Learning
Support vector Machine or SVM is a Supervised Learning algorithm, which is used for Classification and Regression problems. However, primarily, it is used for classification problems in Machine Learning. The goal of the SVM algorithm is to create the decision boundary that can segregate n-dimensional space into classes so that we can easily classify new…
Read MoreDifference between Logistic Regression and Support Vector Machine?
Logistic Regression It is a statistical technique used to model the relationship between one response variable and one or more explanatory variables. It can be used to predict the probability of an event occurring by fitting data into logistic functions. Support Vector Machine It is a supervised machine learning algorithm used for classification and regression…
Read MoreWhat are the most important supervised and unsupervised algorithms?
Supervised Learning algorithms: K-nearest neighbors Linear regression Naïve Bayes Support vector machines Logistic regression Decision trees and random forests K-nearest neighbors: K-nearest neighbors is a Machine learning technique which comes under supervised learning. This technique can be used for classification or regression problems. In supervised learning, we need to specify a target value for the…
Read More