KEEL: Knowledge Extraction based on Evolutionary Learning
Edit Page
Report
Scan day: 07 February 2014 UTC
10
Virus safety - good
Description: The aim of this project is to develop a Computational Environment for integrating the design and use of knowledge extraction models from data using evolutionary algorithms. Genetic learning may also be applied to the model. [GPL]
KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on) ) Java software tool to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering, pattern mining and so on. It contains a big collection of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, etc.), Computational Intelligence based learning algorithms, including evolutionary rule learning algorithms based on different approaches (Pittsburgh, Michigan and IRL, ...), and hybrid models such as genetic fuzzy systems, evolutionary neural networks, etc. It allows us to perform a complete analysis of any learning model in comparison to existing ones, including a statistical test module for comparison. Moreover, KEEL has been designed with a double goal: research and educational. For a detailed description, see the section
Size: 1035 chars
Contact Information
Email: —
Phone&Fax: —
Address: —
Extended: —
WEBSITE Info
| Page title: | KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on) |
| Keywords: | KEEL Project, Data Set, Publication, Learning, Genetic, Rule, Knowledge, Extraction, Evolutionary, Interpretability, Analysis of Algorithms Experimental Design, Analysis of Data Complexity, Association Rules, Interval Rule Based Systems, Discretization, Evolutionary RBF, Feature Selection, Fuzzy Rule Based Systems, Prototype Selection, Instance Selection, Learning from Imbalanced Data, Intervalar Rule Learning, Neural Networks, Missing Values, Subgroup Discovery |
| Description: | KEEL contains classical knowledge extraction algorithms, preprocessing techniques, Computational Intelligence based learning algorithms, evolutionary rule learning algorithms, genetic fuzzy systems, evolutionary neural networks, etc. |
| IP-address: | 150.214.190.154 |