A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects

229

This paper introduces the 3 rd major release of the KEEL Software. KEEL is an open source Java framework (GPLv3 license) that provides a number of modules to perform a wide variety of data mining tasks. It includes tools to perform data management, design of multiple kind of experiments, statistical analyses, etc. This framework also contains KEEL-dataset, a data repository for multiple learning tasks featuring data partitions and algorithms' results over these problems. In this work, we describe the most recent components added to KEEL 3.0, including new modules for semi-supervised learning, multi-instance learning, imbalanced classification and subgroup discovery. In addition, a new interface in R has been incorporated to execute algorithms included in KEEL. These new features greatly improve the versatility of KEEL to deal with more modern data mining problems.

Section: Introductionmentioning

confidence: 76%

KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

Triguero¹,

González²,

Moyano³

et al. 2017

229

“…The work published by Alcalá and Alonso [31], reveals a thorough study of open source-based fuzzy systems software developed as an aid to decisionmaking. In this study, a taxonomy based on two levels is presented.…”

Section: Computational Intelligence and It Toolsmentioning

confidence: 99%

Project Control and Computational Intelligence: Trends and Challenges

Garcia¹,

Peña²,

Pérez³

et al. 2017

Project monitoring and control by using key performance indicators has become a widespread method for decisionmaking in project-oriented organizations. However, the current schools and IT tools created for this purpose require an upgrade in design due to imprecision, vagueness or uncertainty present in the raw data and changing conditions in management styles. Moreover, the use of proprietary technologies in developing nations represents high costs for governments and obstacles to achieving its technological sovereignty. This paper studies the trends and challenges in project control through computational intelligence methods. It also examines schools and technological tools to manage projects, as well as open source software for the application of computational intelligence techniques over the past decades. Current tendencies and improvement areas, valuing niche markets with high applicability around the thematic goal it is also analyzed. The contribution of this study is related to the predicted necessity of constructing new models and IT tools for project control which integrate machine learning-based approaches and treatment of imprecision, vagueness or uncertainty in the information, using key performance indicators linked to fundamental knowledge areas. The implementation of new libraries for learning evaluation in project control with open source software tools, opens a field of research related to increase technological integration with IT project management tools. The content under discussion provides support to improve decision-making in project-oriented organizations.

“…We followed these guidelines to analyze the main strength points of FISDeT. Regarding interoperability, it is widely admitted by the fuzzy community that there is a need for a universal standard language to foster the interoperability of software for fuzzy system development 18 . Since FISDeT uses the FCL language to define fuzzy systems, it allows to exchange fuzzy systems across different platforms and …”

Section: Related Workmentioning

confidence: 99%

“…The novelty of a newly developed tool requires a previous analysis based on the functionality criteria of the existing software in the literature to enable researchers to identify the software needs that the current software cannot provide 18 . We have carried out a preliminary analysis of the existing software in the literature according to basic characteristics such as programming language, interoperability, GUI, use of FCL, general/special purpose, open-source.…”

Section: Related Workmentioning

confidence: 99%

FISDeT: Fuzzy Inference System Development Tool

Castellano¹,

Castiello²,

Pasquadibisceglie³

et al. 2017

This paper introduces FISDeT, a tool to support the design of Fuzzy Inference Systems, composed of a set of Python modules sharing the standard specification language FCL used for FIS definition. FISDeT includes a graphical user interface that enables easy definition and quick update of elements composing the knowledge base of a FIS. Given the knowledge base, the tool can perform the inference of fuzzy rules, providing the output of a FIS for any given input. Modules for creating a fuzzy rule base for classification and verifying the behavior of the classification system are integrated within the environment. The paper also reports applications of FISDeT to acquire available knowledge bases and create a FIS for an image processing task.