Our fourth author, John Platt, gives us a practical guide and a new technique for implementing the algorithm efficiently. Published in: IEEE Intelligent Systems ...

Sep 30, 2020 · This paper provides a brief introduction of SVMs, describes many applications and summarizes challenges and trends. Furthermore, limitations of ...

Application of SVM to medical decision support. The paper (Veropoulos et al ... The study employs KNN, SVM, and LR algorithms as base classifiers ...

Support vector machine (SVM) as a learning machine has shown a good learning ability and generalization ability in classification, regression and forecasting.

A Support Vector Machine, or SVM, is a non-parametric supervised learning model. For non-linear classification and regression, they utilise the kernel trick ...

This paper introduces the basic theory of support vector machine, the basic idea of the classification and currently used support vector machine classification ...

In this paper, a novel learning method, Support Vector Machine (SVM), is applied on different data (Diabetes data, Heart Data, Satellite Data and Shuttle data) ...

We shall use text classification as a running example throughout this paper. ... SVM Active Learning with Applications to Text Classification labeling.

This paper explores the use of Support Vector Machines. (SVMs) for learning text classifiers from examples. It analyzes the par- ticular properties of ...