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KEEL (Knowledge Extraction based on Evolutionary Learning) is an open source (GPLv3) Java software tool that can be used for a large number of different knowledge data discovery tasks.
Category
Data Mining Software Free
Features
•Evolutionary Algorithms (EAs) •Data pre-processing algorithms •Statistical library •User-friendly interface, oriented to the analysis of algorithms. •Allows to create experiments in on-line mode, aiming an educational support in order to learn the operation of the algorithms included. •Knowledge Extraction Algorithms Library. The main employment lines are: •Different evolutionary rule learning models have been implemented •Fuzzy rule learning models with a good trade-off between accuracy and interpretability. •Evolution and pruning in neural networks, product unit neural networks, and radial base models. •Genetic Programming: Evolutionary algorithms that use tree representations for extracting knowledge. •Algorithms for extracting descriptive rules based on patterns subgroup discovery have been integrated. •Data reduction (training set selection, feature selection and discretization). EAs for data reduction have been included.
License
Open Source
Price
Free
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
•Allows to create experiments in on-line mode, aiming an educational support in order to learn the operation of the algorithms included. •Knowledge Extraction Algorithms Library. The main employment lines are: •Different evolutionary rule learning models have been implemented •Fuzzy rule learning models with a good trade-off between accuracy and interpretability. •Evolution and pruning in neural networks, product unit neural networks, and radial base models. •Genetic Programming: Evolutionary algorithms that use tree representations for extracting knowledge.
What are the benefits?
• Data management • Design of experiments • Design of imbalanced experiments • Experimentation with multiple instance learning algorithms • Experimentation with semi-supervised learning algorithms • Statistical tests • Educational experiments
PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
6.6
Features & Functionality
7.6
8.2
Advanced Features
7.6
8.2
Integration
7.6
6.5
Performance
7.6
7.9
Customer Support
7.6
8.3
Implementation
8.2
Renew & Recommend
8.0
Bottom Line
KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms.
7.6
Editor Rating
7.8
Aggregated User Rating
2 ratings
You have rated this
KEEL (Knowledge Extraction based on Evolutionary Learning) is an open source (GPLv3) Java software tool that can be used for a large number of different knowledge data discovery tasks. KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms.
It contains a wide variety of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, among others), computational intelligence based learning algorithms, hybrid models, statistical methodologies for contrasting experiments and so forth.
It allows to perform a complete analysis of new computational intelligence proposals in comparison to existing ones. Moreover, KEEL has been designed with a two-fold goal: research and educational.
KEEL is a software tool to assess EAs for DM problems including regression, classification, clustering, pattern mining and so on. KEEL is an integration of an environment with a defined architecture and a development of knowledge extraction as expandable modules.
The researcher tool is used in automated execution of experiments, and the statistical analysis of their results. Routinely, an experimental design includes a mix of evolutionary algorithms, statistical and AI-related techniques.
Special care was taken to make possible that a researcher can use KEEL to assess the relevance of his own procedures. The educational tool is a simplified version of the research tool, where only the most relevant algorithms are available. The execution is made in real time.
The user has a visual feedback of the progress of the algorithms, and can access the final results from the same interface used to design the experimentation. Both types of user require an availability of a set of features in order to be interested in using KEEL.
Nice and simple user interface based on data flow.
What is best?
KEEL also has another feature that allows a researcher to address classification with multiple instance datasets. KEEL also provides a researcher with a complete set of statistical procedures so as to perform multiple comparisons. KEEL is mainly designed as a research and educational tool.
Company size
Medium (50 to 1000)
User Role
Super User
User Industry
Pharmaceutical
Rating
Ease of use8
KEEL (Knowledge extraction based on evolutionary learning) is an open source tool that is used for a variety of data discovery tasks. KEEL provides a very nice and simple user interface based on data flow. It allows for designing of experiments using a variety of datasets and computational intelligence algorithms. This is done so as to ensure assess of the behavior of algorithms. KEEL provides an excellent way to perform a complete analysis of any new computational intelligence proposals which will be compared to already existing ones. KEEL has a feature that provides
Features & Functionality8.2
Advanced Features8.2
Integration8.2
Performance7.9
Training 8.3
Customer Support8.3
Implementation8.2
Renew & Recommend8
ADDITIONAL INFORMATION KEEL has a feature that provides an excellent way to design experiments over specific datasets. It provides an experiment graph showing the components of the experiment that is currently there and subsequently helps to describe the different relationships between them.
Nice and simple user interface based on data flow.
KEEL also has another feature that allows a researcher to address classification with multiple instance datasets. KEEL also provides a researcher with a complete set of statistical procedures so as to perform multiple comparisons. KEEL is mainly designed as a research and educational tool.
Medium (50 to 1000)
Super User
Pharmaceutical
KEEL (Knowledge extraction based on evolutionary learning) is an open source tool that is used for a variety of data discovery tasks. KEEL provides a very nice and simple user interface based on data flow. It allows for designing of experiments using a variety of datasets and computational intelligence algorithms. This is done so as to ensure assess of the behavior of algorithms. KEEL provides an excellent way to perform a complete analysis of any new computational intelligence proposals which will be compared to already existing ones. KEEL has a feature that provides
ADDITIONAL INFORMATION
KEEL has a feature that provides an excellent way to design experiments over specific datasets. It provides an experiment graph showing the components of the experiment that is currently there and subsequently helps to describe the different relationships between them.