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 …

We present an integrated algorithm for simultaneous feature selection (FS) and designing of
diverse classifiers using a steady state multiobjective genetic programming (GP), which …

In an emergency evacuation operation, accurate classification of the evacuee population
can provide important information to support the responders in decision making; and …

The objectives of this paper are to investigate the capability of genetic programming to select
and extract linearly separable features when the evolutionary process is guided to achieve …

Multiclass classification is one of the most fundamental tasks in data mining. However,
traditional data mining methods rely on the model assumption, they generally can suffer from …

In the multi-class classification problem GP plays an important role when combined with
other non-GP classifiers. However, when GP performs the actual classification (without …

This paper introduces a two-stage strategy for multi-class classification problems. The
proposed technique is an advancement of tradition binary decomposition method. In the first …

Genetic Programming (GP) provides a novel way of classification with key features like
transparency, flexibility and versatility. Presence of these properties makes GP a powerful …

The important problem of data classification spans numerous real life applications. The
classification problem has been tackled by using Genetic Programming in many successful …

This paper presents a regularization method for program complexity control of linear genetic
programming tuned for transcendental elementary functions. Our goal is to improve the …