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  2. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...

  3. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    scikit-learn – extends SciPy with a host of machine learning models (classification, clustering, regression, etc.) Shogun (toolbox) – open-source, large-scale machine learning toolbox that provides several SVM (Support Vector Machine) implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R

  4. scikit-multiflow - Wikipedia

    en.wikipedia.org/wiki/Scikit-multiflow

    The scikit-multiflow library is implemented under the open research principles and is currently distributed under the BSD 3-clause license. scikit-multiflow is mainly written in Python, and some core elements are written in Cython for performance. scikit-multiflow integrates with other Python libraries such as Matplotlib for plotting, scikit-learn for incremental learning methods [4 ...

  5. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    One of the early open-source AI frameworks was Scikit-learn, released in 2007. [28] Scikit-learn became one of the most widely used libraries for machine learning due to its ease of use and robust functionality, providing implementations of common algorithms like regression, classification, and clustering.

  6. TPS report - Wikipedia

    en.wikipedia.org/wiki/TPS_report

    A mock-up of a TPS report cover sheet, created for the movie Office Space. A TPS report ("test procedure specification") is a document used by a quality assurance group or individual, particularly in software engineering, that describes the testing procedures and the testing process.

  7. 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 ...

  8. Conjoint analysis - Wikipedia

    en.wikipedia.org/wiki/Conjoint_analysis

    Example choice-based conjoint analysis survey with application to marketing (investigating preferences in ice-cream) Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes (feature, function, benefits) that make up an individual product or service.

  9. 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.

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