Data Mining Tools
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RapidMiner
RapidMiner – An Open Source Data Mining Tool
RapidMiner is an Open Source Data Mining Tool used for the purpose of machine learning, data mining, text mining, predictive analytics and business analytics. RapidMiner can easily integrate your own specialized algorithms by leveraging its powerful and open extension APIs. RapidMiner Studio breaks away from the limitations of traditional data analysis tools and allows you to work with large data sources for In-memory, in-database and in-Hadoop analytics for every size data source.
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KNIME
KNIME – An Open Source Data Mining Tool
KNIME also called as Konstanz Information Miner is an Open Source Data Mining Tool Used for data analytics, reporting and integration platform. The modular data pipelining concept of KNIME integrates various components for machine learning and data mining. It can also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.
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Apache Mahout
Apache Mahout-An Open Source Data Mining Tool
Apache Mahout is an Open Source data Ming Tool which is designed to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification. Mahout also provides Java libraries for common mathematics operations and primitive Java collections.
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Keel
Keel– An Open Source Data Mining Tool
Keel is an open Source Data Mining Tool used to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering and pattern mining. It also allows us to perform a complete analysis of any learning model in comparison to existing ones, including a statistical test module for comparison.
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RATTLE
RATTLE - An Open Source Data Mining Tool
Togaware developed an Open Source Data Mining Tool called RATTLE that presents statistical and visual summaries of data, transforms data into forms that can be readily modeled, builds both unsupervised and supervised models from the data, presents the performance of models graphically, and scores new datasets.
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