This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

Distributed denial-of-service attacks are still difficult to handle as per current scenarios. The
attack aim is a menace to network security and exhausting the target networks with …

We study problems of optimization of decision and inhibitory trees for decision tables with
many-valued decisions. As cost functions, we consider depth, average depth, number of …

This study proposes utilizing deep learning and machine learning techniques to identify
network anomalies. The IoT-23 dataset serves as the basis for the analysis. The proposed …

Decision trees are one of the most commonly used tools in decision analysis, knowledge
representation, machine learning, etc., for its simplicity and interpretability. We consider an …

In this chapter, we study bi-criteria optimization problem cost versus cost for decision and
inhibitory trees. We design an algorithm which constructs the set of Pareto optimal points for …

The exponential growth as well as the availability of data has triggered the development of
data analytics tools to harness the power of information hidden in data. These …

Cluster Deletion (CD) problem asks to transform a given graph into a cluster graph by at
most k edge deletions. CD is a combinatorial problem arising in the field of classification. In …