Software
We've compiled a list of 5 free and paid alternatives to KEEL. The primary competitors include Orange Data Mining, WEKA. In addition to these, users also draw comparisons between KEEL and Apache Mahout, GMDH Streamline (GMDH Shell), Actian. Also you can look at other similar options here: Education and Reference Software.
We've compiled a list of 5 free and paid alternatives to KEEL. The primary competitors include Orange Data Mining, WEKA. In addition to these, users also draw comparisons between KEEL and Apache Mahout, GMDH Streamline (GMDH Shell), Actian. Also you can look at other similar options here: Education and Reference Software.
Open-source software for visual data analysis and machine learning. It is developed in the Python programming language and provides an intuitive graphical user interface. Orange provides a wide range of tools for working with data, including visuali…
Weka is an open-source machine learning software for data mining tasks. It provides tools for classification, regression, clustering, and association rule mining. Weka features a user-friendly interface and supports multiple data formats for researc…
Boost supply chain efficiency with advanced analytics and machine learning. Automate real-time data analysis for precise demand forecasting and inventory optimization.
KEEL is an open source (GPLv3) Java software tool to assess evolutionary algorithms for Data Mining...
KEEL is an open source (GPLv3) Java software tool to assess evolutionary algorithms for Data Mining...
Linux
Mac
Windows
KEEL is an open source (GPLv3) 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.
Data Mining
Clustering
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