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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    t. e. Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. [1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from ...

  3. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R (programming language) R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics, and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.

  4. Text mining - Wikipedia

    en.wikipedia.org/wiki/Text_mining

    Text mining. Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails ...

  5. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ naɪm / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept. A graphical user interface and use of JDBC allows assembly ...

  6. Weka (software) - Wikipedia

    en.wikipedia.org/wiki/Weka_(software)

    Weka (software) Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License. It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques".

  7. Orange (software) - Wikipedia

    en.wikipedia.org/wiki/Orange_(software)

    Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.

  8. Predictive Model Markup Language - Wikipedia

    en.wikipedia.org/wiki/Predictive_Model_Markup...

    Type of format. Predictive modelling. Extended from. XML. The Predictive Model Markup Language (PMML) is an XML -based predictive model interchange format conceived by Robert Lee Grossman, then the director of the National Center for Data Mining at the University of Illinois at Chicago. PMML provides a way for analytic applications to describe ...

  9. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...