Feature selection aims at selecting important features that can enhance learning
performance in data mining, pattern recognition, and machine learning. Filter feature …

Now a day, all the organizations collecting huge volume of data without knowing its
usefulness. The fast development of Internet helps the organizations to capture data in many …

Intrusion detection systems (IDSs) play an important role in the security of computer
networks. One of the main challenges in IDSs is the high-dimensional input data analysis …

The feature selection process constitutes a commonly encountered problem of global
combinatorial optimization. The process reduces the number of features by removing …

We propose an optimized Support Vector Machine classifier, named PMSVM, in which
System Normalization, PCA, and Multilevel Grid Search methods are comprehensively …

By Emerging huge databases and the need to efficient learning algorithms on these
datasets, new problems have appeared and some methods have been proposed to solve …

This paper will demonstrate a machine learning application for predicting positive lead
conversion events on the Edmunds. com website, an American destination for car shopping …

Feature selection technique has been a very active research topic that addresses the
problem of reducing the dimensionality. Whereas, datasets are continuously growing over …

Today, detecting anomalous traffic and preventing it in computer networks has become
increasingly important for the community of security researchers. An intrusion detection …

Abstract The Internet of Things (IoT) is a worldwide network including all identifiable
heterogeneous objects around us such as smartphones, laptops or smart sensors that can …