Support Vector Machines

Support-Vector-Machines

Support Vector Machines (SVMs) are a powerful supervised learning algorithm primarily used for classification tasks, though they can also be applied to regression problems. SVMs work by identifying the optimal hyperplane that separates different classes in a dataset, maximizing the margin between the closest data points, known as support vectors. This approach makes SVMs particularly effective for high-dimensional data and complex datasets, promoting good generalization while minimizing the risk of overfitting. With various kernel functions available, SVMs can adapt to different types of data distributions, making them versatile tools in machine learning applications.

Analytics Vidhya

In machine learning, support vector machines are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. Given a set of…

1.4. Support Vector Machines

Scikit-learn User Guide

Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection. The advantages of support vector machines are: Effective in high ......

Support Vector Machines

Codecademy

Support Vector Machines (SVMs) are a supervised learning algorithm excelling at classification tasks. They work by finding the optimal hyperplane that maximizes the margin between different classes in...

Support Vector Machines Explained

Python in Plain English

Support Vector machines are a common supervised machine learning algorithm used in both classification and regression problems, however are most commonly used for classification which will be the…

The Basics: Support Vector Machines

Towards Data Science

Support vector machines are a type of machine learning model used for classification that has proven to be very popular since their wider introduction in the ’90s. Somewhat confusingly, the names…

Support Vector Machine (SVM)

Analytics Vidhya

Support Vector Machine (SVM). Support Vector Machine (SVM) is a supervised classifier and is defined by a separating hyperplane. In other words, given a set of labeled….

What is Support Vector Machine?

Towards Data Science

Support Vector Machine (SVM) is a supervised machine learning algorithm. SVM’s purpose is to predict the classification of a query sample by relying on labeled input data which are separated into two…...

Explain Support Vector Machines in Mathematic Details

Towards Data Science

Support Vector Machine(SVM) is a supervised machine learning algorithm that is usually used in solving binary classification problems. It can also be applied in multi-class classification problems…

In-Depth: Support Vector Machines

Python Data Science Handbook

Support vector machines (SVMs) are a particularly powerful and flexible class of supervised algorithms for both classification and regression. In this section, we will develop the intuition behind sup...

SUPPORT VECTOR MACHINES(SVM)

Towards Data Science

Support Vector Machine are perhaps one of the most popular and talked about machine learning algorithms.They were extremely popular around the time they were developed in the 1990s and continue to be…...

Support Vector Machine — Explained

Towards Data Science

Support Vector Machine (SVM) is a supervised machine learning algorithm which is mostly used for classification tasks. It is suitable for regression tasks as well. Supervised learning algorithms try…

What is the Support Vector Machine (SVM)

Analytics Vidhya

Support Vector Machine (SVM) is a supervised machine learning algorithm. That can be employed for both classification and regression purposes. It uses a technique called the kernel trick to transform…...