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  2. Weka (software) - Wikipedia

    en.wikipedia.org/wiki/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". [1]

  3. Massive Online Analysis - Wikipedia

    en.wikipedia.org/wiki/Massive_Online_Analysis

    Massive Online Analysis (MOA) is a free open-source software project specific for data stream mining with concept drift. It is written in Java and developed at the University of Waikato, New Zealand. [2]

  4. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), 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.

  5. SPSS Modeler - Wikipedia

    en.wikipedia.org/wiki/SPSS_Modeler

    In 1998 ISL was acquired by SPSS Inc., who saw the potential for extended development as a commercial data mining tool. In early 2000, the software was developed into a client–server model architecture, and shortly afterward, the client front-end interface component was rewritten fully and replaced with a new Java front-end, which allowed ...

  6. Rattle GUI - Wikipedia

    en.wikipedia.org/wiki/Rattle_GUI

    Rattle GUI is a free and open source software (GNU GPL v2) package providing a graphical user interface (GUI) for data mining using the R statistical programming language. Rattle is used in a variety of situations.

  7. C4.5 algorithm - Wikipedia

    en.wikipedia.org/wiki/C4.5_algorithm

    In 2011, authors of the Weka machine learning software described the C4.5 algorithm as "a landmark decision tree program that is probably the machine learning workhorse most widely used in practice to date". [2] It became quite popular after ranking #1 in the Top 10 Algorithms in Data Mining pre-eminent paper published by Springer LNCS in 2008. [3]

  8. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one.

  9. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    Data mining is a highly effective tool in the catalog marketing industry. [citation needed] Catalogers have a rich database of history of their customer transactions for millions of customers dating back a number of years. Data mining tools can identify patterns among customers and help identify the most likely customers to respond to upcoming ...