Network intrusion is a growing threat with potentially severe impacts, which can be
damaging in multiple ways to network infrastructures and digital/intellectual assets in the …

Tumor classification based on gene expression levels is important for tumor diagnosis.
Since tumor data in gene expression contain thousands of attributes, attribute selection for …

Brain tumor is one of the most harmful diseases, and has affected majority of people
including children in the world. The probability of survival can be enhanced if the tumor is …

Many search strategies have been exploited for the task of feature selection (FS), in an effort
to identify more compact and better quality subsets. Such work typically involves the use of …

Early diagnosis of malignant leukemia can enormously help the physicians in choosing the
right treatment for the patient. A lot of diagnostic techniques are available to identify …

There are mainly two methodologies dealing with uncertainty measurement issue in rough
set theory: pure rough set approach and information theory approach. Pure rough set …

Feature selection plays a vital role in many areas of pattern recognition and data mining.
The effective computation of feature selection is important for improving the classification …

Uncertainty measures can supply new viewpoints for analyzing data. They can help us in
disclosing the substantive characteristics of data. The uncertainty measurement issue is also …

Feature Selection (FS) or Attribute Reduction techniques are employed for dimensionality
reduction and aim to select a subset of the original features of a data set which are rich in the …

Among the large amount of genes presented in microarray gene expression data, only a
small fraction of them is effective for performing a certain diagnostic test. In this regard, a …