The evaluation of feature selection methods for text classification with small sample datasets
must consider classification performance, stability, and efficiency. It is, thus, a multiple …

Rank aggregation (RA), the process of combining multiple ranked lists into a single ranking,
has played an important role in integrating information from individual genomic studies that …

Sažetak Obtaining meaningful information from data has become the main problem. Hence
data mining techniques have gained importance. Text classification is one of the most …

Text categorization is the task of automatically assigning unlabeled text documents to some
predefined category labels by means of an induction algorithm. Since the data in text …

Univariate feature rankers have been frequently used to order genes (features) in terms of
their importance to a given bioinformatics challenge. Unfortunately, the resulting feature …

This work deals with document classification. It is a supervised learning method (it needs a
labeled document set for training and a test set of documents to be classified). The …

A very promising tool for data mining and bioinformatics is ensemble gene (feature)
selection. Ensemble feature selection is the process of performing multiple runs of feature …

The process of accommodating data is limited by the evolution of hardware and
technologies, and the current analytical tools are not sufficient enough to retrieve information …

Feature selection is a crucial machine learning technique aimed at reducing the
dimensionality of the input space. By discarding useless or redundant variables, not only it …

Purpose Multi-label Text Classification (MTC) is one of the most recent research trends in
data mining and information retrieval domains because of many reasons such as the rapid …