In the area of pattern recognition and machine learning, features play a key role in
prediction. The famous applications of features are medical imaging, image classification …

Data preprocessing is a major and essential stage whose main goal is to obtain final data
sets that can be considered correct and useful for further data mining algorithms. This paper …

The volume of data on the social media is huge and even keeps increasing. The need for
efficient processing of this extensive information resulted in increasing research interest in …

Classical fuzzy rough set often uses fuzzy rough dependency as an evaluation function of
feature selection. However, this function only retains the maximum membership degree of a …

When tackling high dimensionality in data mining, online feature selection which deals with
features flowing in one by one over time, presents more advantages than traditional feature …

Gene selection is crucial to tumor identification based on microarray expression data. The
identification of genes with strong discriminative power has been a hot research topic and a …

Interacting features are those that appear to be irrelevant or weakly relevant with the class
individually, but when it combined with other features, it may highly correlate to the class …

Feature selection is an important preprocessing step in machine learning and data mining.
In real-world applications, costs, including money, time and other resources, are required to …

With the development of bioinformatics, tumor classification from gene expression data
becomes an important useful technology for cancer diagnosis. Since a gene expression …

Online streaming feature selection, as a new approach which deals with feature streams in
an online manner, has attracted much attention in recent years and played a critical role in …