Learn how to use a support vector machine (SVM) to design an AI algorithm for anomaly detection, and what are the challenges and benefits of this approach. Skip to main content LinkedIn Articles ...

A Support Vector Machine (SVM) is a supervised learning algorithm utilized in the field of machine learning. It is primarily applied to perform tasks such as classification and regressionThis ...

In this repository, you will find a comprehensive collection of in-depth explanations, intuition, questions, and answers related to the Support Vector Machine (SVM) algorithm. Additionally, you will ...

Vehicular Ad-hoc Networks (VANETs) are known to be very susceptible to various malicious attacks. To detect and mitigate these malicious attacks, many security mechanisms have been studied for VANETs.

This paper presents a solution to the problem of classifying large datasets via learning of the data topology. The described algorithm combines the GNG algorithm with the SVM solver into a specific ...

It also covers the use of clustering techniques (DBSCAN) on latent features and the application of a one-class support vector machine (OC-SVM) for outlier detection in the sub-algorithm. To create a ...

Computational Complexity: Training SVM can be computationally expensive, especially for large datasets. Difficulty in Interpreting Results: SVM models can be difficult to interpret, especially when ...