Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …

Lung cancer is a potentially lethal illness. Cancer detection continues to be a challenge for
medical professionals. The true cause of cancer and its complete treatment have still not …

Featured Application The paper analyzes the usage and mechanisms of feature selection
methods that are based on swarm intelligence in different application areas. Abstract The …

Accurate classification of high-dimensional biomedical data highly depends on the efficient
recognition of the data's main features which can be used to assist diagnose related …

Cancer is a group of diseases caused due to abnormal cell growth. Due to the innovation of
microarray technology, a large variety of microarray cancer datasets are produced and …

Analysis of microarray data is a highly challenging problem due to the inherent complexity in
the nature of the data associated with higher dimensionality, smaller sample size …

This paper presents an effective metaheuristic algorithm called teaching learning-based
optimization which is widely applied to solve the various real-world optimization problems …

Cancer prediction in the early stage is a topic of major interest in medicine since it allows
accurate and efficient actions for successful medical treatments of cancer. Mostly cancer …