Ensemble learning is a prolific field in Machine Learning since it is based on the assumption
that combining the output of multiple models is better than using a single model, and it …

Gene Expression is the process of determining the physical characteristics of living beings
by generating the necessary proteins. Gene Expression takes place in two steps, translation …

In the last decade, ensemble learning has become a prolific discipline in pattern recognition,
based on the assumption that the combination of the output of several models obtains better …

Electronic nose (e-nose) systems have been reported to be used in many areas as rapid,
low-cost, and non-invasive instruments. Especially in meat production and processing, e …

Feature selection ensemble methods are a recent approach aiming at adding diversity in
sets of selected features, improving performance and obtaining more robust and stable …

Gene microarray technology can detect many gene expressions simultaneously, which is
essential for disease diagnosis. However, microarray data are usually characterized by …

In the last decade, there has been a growing scientific interest in the analysis of DNA
microarray datasets, which have been widely used in basic and translational cancer …

To mitigate the curse of dimensionality in high-dimensional datasets, feature selection has
become a crucial step in most data mining applications. However, no feature selection …

In an electronic nose (e-nose) system, the gas sensor array is the key component for
detecting the volatile profile of a sample. An inappropriate sensor combination can lead to …

Classically, machine learning methods have used a single learning model to solve a given
problem. However, the technique of using multiple prediction models for solving the same …