The field of data mining is concerned with knowledge discovery from data through the development of computer programs. During the last two decades, the rapid advances in data acquisition capacity and database technology have led to the production of datasets with large numbers of features in many fields. Most of the features are irrelevant and redundant, and these unnecessary features have stimulated a phenomenon in the data mining methods. Therefore, feature selection is an important and active research area in data preprocessing. Feature selection is the process of identifying a subset of relevant features in an original feature set.
Universal Feature Selection Tool (UniFeat) is an open-source tool entirely developed in Java for performing feature selection process in different areas of research.
UniFeat is principally implemented and developed at the University of Kurdistan, Iran, and distributed under the MIT License terms.
UniFeat provides a set of well-known and state-of-the-art feature selection methods within its practical auxiliary tools, including performance evaluation, results visualization, statistical analysis, and reduced datasets to compare the performance of feature selection methods.