SVM classification - Learn Data Science with Travis

SVM-classification

Support Vector Machine (SVM) classification is a powerful supervised learning algorithm used for categorizing data into distinct classes. It operates by identifying the optimal hyperplane that separates different categories in a high-dimensional space, maximizing the margin between the closest data points of each class, known as support vectors. SVM is particularly effective in handling both linear and non-linear classification tasks through the use of kernel functions, which transform the input data into higher dimensions. Its robustness against overfitting makes it a popular choice for various applications in machine learning and data science.

SVM (Support Vector Machine) for classification

Towards Data Science

SVM: Support Vector Machine is a supervised classification algorithm where we draw a line between two different categories to differentiate between them. SVM is also known as the support vector…

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….

Road to SVM: Maximal Margin Classifier and Support Vector Classifier

Analytics Vidhya

Support Vector Machine is a popular Machine Learning algorithm used in classification tasks, especially for its adaptability to non-linearly separable data (thanks to the so-called Kernel trick)…

Multiclass Classification with Support Vector Machines (SVM), Kernel Trick & Kernel Functions

Towards Data Science

Support Vector Machines (SVM) are not new but are still a powerful tool for classification due to their tendency not to overfit, but to perform well in many cases. If you are only interested in a…

A brief Introduction to Support Vector Machine

Towards Data Science

Support Vector Machine (SVM) is one of the most popular Machine Learning Classifier. It falls under the category of Supervised learning algorithms and uses the concept of Margin to classify between…

Introduction to SVM and Kernel Trick — Part 1 (Theory)

Analytics Vidhya

Support Vector Machine (SVM) is a type of algorithm for classification and regression in supervised learning contained in machine learning, also known as support vector networks. SVM is more commonly…...

An Introduction to Support Vector Machine

Towards Data Science

SVM is a supervised machine learning algorithm that is used for both classification and regression problems. SVM is used for both linear separable data and non-linear separable data. For non-linear…

What is the Support Vector Machine (SVM)

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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…...

Decoding Support Vector Machines

Towards Data Science

SVM is a very simple yet powerful supervised machine learning algorithm that can be used for classification as well as regression though its popularly used for classification. They perform really…

Fully Explained SVM Classification with Python

Towards AI

In this article, we will discuss the most used machine learning algorithm in classification problems. The support vector machine (SVM) algorithm is used for regression, classification, and also for…

The Support Team — SVM

Towards Data Science

A Support Vector Machine (SVM) is a very powerful and versatile Machine Learning model. SVM can be used for classification or regression problem and outlier detection. It is one of the most popular…

Support Vector Machine(SVM) and the multi-dimensional wizardry

Towards Data Science

Data Science|Machine Learning|Algorithms Learn the magic behind the kernel functions in SVMs Support Vector Machine (SVM) is a supervised learning algorithm used for regression, classification, and o...