Classification is one of the most researched questions in machine learning and data mining.
A wide range of real problems have been stated as classification problems, for example …

Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

Feature extraction is the first and most critical step in image classification. Most existing
image classification methods use hand-crafted features, which are not adaptive for different …

This paper presents an online feature selection algorithm using genetic programming (GP).
The proposed GP methodology simultaneously selects a good subset of features and …

Data mining deals with the problem of discovering novel and interesting knowledge from
large amount of data. This problem is often performed heuristically when the extraction of …

Transfer learning (TL) is the process by which some aspects of a machine learning model
generated on a source task is transferred to a target task, to simplify the learning required to …

This paper proposes a novel method called FLGP to construct a classifier device of
capability in feature selection and feature extraction. FLGP is developed with layered …

In this paper we explore the application of Genetic Programming (GP) to the problem of
domain-independent image feature extraction and classification. We propose a new GP …

This paper proposes a method called layered genetic programming (LAGEP) to construct a
classifier based on multi-population genetic programming (MGP). LAGEP employs layer …

In recent years, cyberattacks on humongous networks have resulted in irreversible damages
and financial losses to many organizations and infrastructures. To some extent, an intrusion …