Electroencephalogram (EEG) is the recording of the electrical activity of the brain which can
be used to identify different disease conditions. In the case of a partial epilepsy, some …

The induction of decision trees is a widely-used approach to build classification models that
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …

At present, the study of gene expression data provides a reference for tumor diagnosis at the
molecular level. It is a challenging task to select the feature genes related to the …

Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast,
and low-cost method, has been continuously used for detecting human diseases, including …

Classification is valuable and necessary in spectral analysis, especially for data-driven
mining. Along with the rapid development of spectral surveys, a variety of classification …

Malignancies and diseases of various genetic origins can be diagnosed and classified with
microarray data. There are many obstacles to overcome due to the large size of the gene …

Due to the non-linear but highly interpretable representations, decision tree (DT) models
have significantly attracted a lot of attention of researchers. However, it is difficult to …

The problem of underfitting and overfitting in machine learning is often associated with a
bias-variance trade-off. The underfitting most clearly manifests in the tree-based inducers …

Electroencephalogram (EEG) is the recording of the electrical activity of the brain which can
be used to identify different disease conditions. In the case of a partial epilepsy, some …

This paper proposes a comprehensive approach to explore whether functional brain
network (FBN) changes from the alert state to the drowsy state and to find out ideal …