In this paper, we introduce a new kernel function for improving the accuracy of the Support
Vector Machines (SVMs) classification. The proposed kernel function is stated in general …

With the growing use of biometric authentication systems in the past years, spoof fingerprint
detection has become increasingly important. In this work, we implement and evaluate two …

The goal of this paper is to propose a hybrid technique to improve Support Vector Machines
classification accuracy using training data sampling and hyperparameter tuning. The …

Abstract Support Vector Machine (SVM) is a well-known machine learning classification
algorithm, which has been widely applied to many data mining problems, with good …

In this paper, a universal kernel function is introduced that could improve the classification
accuracy of Support Vector Machines (SVMs) for both linear and nonlinear data sets. A class …

Due to the fast-growing rate of information sources, many organizations and individuals are
overwhelmed with vast amounts of data. The rate of data growth is very alarming, and it is …

Breast cancer detection and prognosis may result in better medication being provided early,
lowering the number of deaths caused by the illness each year and presenting a potentially …

Support vector machines (SVM) together with principal component analysis (PCA) have
been applied to hyperspectral image classification and mapping with great success. PCA …

SVM technique is one of the best techniques to classify data, but it has a slow performance
in the big data arrays. This paper introduces the method to improve the speed of SVM …

Support vector machines (SVMs) have proved to be promising methods for classification and
regression analysis because of their solid mathematical foundations which convey several …