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?
When working on classification tasks, it is important to comprehend the disparities between logistic regression and support vector machine (SVM), two prevalent machine learning techniques with distinct approaches and advantages. In this discourse, we will delve into the contrast between these two algorithms. Logistic Regression Logistic regression is a statistical method employed to model the…
Read MoreImportant Supervised and Unsupervised Algorithms for Machine Learning
Machine learning is a branch of computer science and artificial intelligence that allows machines to learn automatically without special programming. It involves using algorithms and statistical models to analyze and interpret data and make predictions based on that analysis. Machine learning can be broadly divided into two types of algorithms: supervised and unsupervised. In this…
Read More