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  2. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    Daimler-Benz had a significant data mining team. OHRA was starting to explore the potential use of data mining. The first version of the methodology was presented at the 4th CRISP-DM SIG Workshop in Brussels in March 1999, [5] and published as a step-by-step data mining guide later that year. [6]

  3. Group method of data handling - Wikipedia

    en.wikipedia.org/wiki/Group_method_of_data_handling

    Group method of data handling. Group method of data handling (GMDH) is a family of inductive algorithms for computer-based mathematical modeling of multi-parametric datasets that features fully automatic structural and parametric optimization of models. GMDH is used in such fields as data mining, knowledge discovery, prediction, complex systems ...

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical ...

  5. Information retrieval - Wikipedia

    en.wikipedia.org/wiki/Information_retrieval

    Information retrieval is the science [1] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds. Automated information retrieval systems are used to reduce what has been called information overload.

  6. k-anonymity - Wikipedia

    en.wikipedia.org/wiki/K-anonymity

    k -anonymity is an attempt to solve the problem "Given person-specific field-structured data, produce a release of the data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data remain practically useful." [3][4][5] A release of data is said to have the k -anonymity property if ...

  7. Data stream mining - Wikipedia

    en.wikipedia.org/wiki/Data_stream_mining

    Data Stream Mining (also known as stream learning) is the process of extracting knowledge structures from continuous, rapid data records. A data stream is an ordered sequence of instances that in many applications of data stream mining can be read only once or a small number of times using limited computing and storage capabilities. [1] In many ...

  8. 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 ...

  9. 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 ...