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Weka
Weka, an open source software, is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data set or called from the user's own JAVA code (as Weka itself has been fully implemented in the JAVA programming language). Weka features include machine learning, data mining, pre-processing, classification, regression, clustering, association rules, attribute selection, experiments, workflow and visualisation
Type of content:
Assets
Type of asset:
Application / Tool
Big data potential
Yes
Policy domains:
Innovation, Science & Technology
Phase in the policy cycle:
Policy Design and Analysis
TRL
7
Open license availability
Yes
Website
Serves:
Addresses:
| SWOT Analysis for Weka |
||
|---|---|---|
| Helpful | Harmful | |
Internal |
Strengths• Weka is data mining software that uses a collection of machine learning algorithms. These algorithms can be applied directly to the data or called from the Java code. • Platform Independent • Open source and free • Three graphical User’s interfaces • Flexibility for scripting experiments. |
Weaknesses• The visualization of data, results, and processes is not highly colourful or as detailed as other data mining software packages • Low ease of use • TRL • "Java's insanely complex, difficult and unintuitive installation" process • Java lacks a few features that some C++ programmers find useful, for example, macros and operator overloading |
External |
Opportunities• The program can be used in many areas, such as natural sciences, engineering, modelling and analysis of financial markets • High demand on tools that help extracting insight from big data: The enterprise-generated data is expected to exceed 240 exabytes daily by 2020 |
Threats• Open source software is much more vulnerable to security holes, since the code is open to everyone. |
