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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data. In contrast, data mining uses machine learning and statistical models to uncover clandestine or hidden patterns in a large ...

  3. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    Spatial data mining is the application of data mining methods to spatial data. The end objective of spatial data mining is to find patterns in data with respect to geography. So far, data mining and Geographic Information Systems (GIS) have existed as two separate technologies, each with its own methods, traditions, and approaches to ...

  4. Oracle Data Mining - Wikipedia

    en.wikipedia.org/wiki/Oracle_Data_Mining

    Oracle Data Mining (ODM) is an option of Oracle Database Enterprise Edition. It contains several data mining and data analysis algorithms for classification, prediction, regression, associations, feature selection, anomaly detection, feature extraction, and specialized analytics.

  5. 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.

  6. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    The base data and the dimension tables are stored as relational tables and new tables are created to hold the aggregated information. It depends on a specialized schema design. This methodology relies on manipulating the data stored in the relational database to give the appearance of traditional OLAP's slicing and dicing functionality.

  7. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    ELKI – Data mining framework in Java with data mining oriented visualization functions. KNIME – The Konstanz Information Miner, a user friendly and comprehensive data analytics framework. Orange – A visual programming tool featuring interactive data visualization and methods for statistical data analysis, data mining, and machine learning.

  8. Rattle GUI - Wikipedia

    en.wikipedia.org/wiki/Rattle_GUI

    Rattle provides considerable data mining functionality by exposing the power of the R Statistical Software through a graphical user interface. Rattle is also used as a teaching facility to learn the R software Language. There is a Log Code tab, which replicates the R code for any activity undertaken in the GUI, which can be copied and pasted.

  9. Weka (software) - Wikipedia

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

    A comprehensive collection of data preprocessing and modeling techniques. Ease of use due to its graphical user interfaces. Weka supports several standard data mining tasks, more specifically, data preprocessing, clustering, classification, regression, visualization, and feature selection. Input to Weka is expected to be formatted according the ...