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  2. XGBoost - Wikipedia

    en.wikipedia.org/wiki/XGBoost

    XGBoost. XGBoost[2] (eXtreme Gradient Boosting) is an open-source software library which provides a regularizing gradient boosting framework for C++, Java, Python, [3] R, [4] Julia, [5] Perl, [6] and Scala. It works on Linux, Microsoft Windows, [7] and macOS. [8] From the project description, it aims to provide a "Scalable, Portable and ...

  3. LightGBM - Wikipedia

    en.wikipedia.org/wiki/LightGBM

    LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. [4][5] It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and scalability.

  4. Boosting (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Boosting_(machine_learning)

    Machine learningand data mining. In machine learning (ML), boosting is an ensemble metaheuristic for primarily reducing bias (as opposed to variance). [1] It can also improve the stability and accuracy of ML classification and regression algorithms. Hence, it is prevalent in supervised learning for converting weak learners to strong learners.

  5. CatBoost - Wikipedia

    en.wikipedia.org/wiki/Catboost

    catboost.ai. CatBoost[6] is an open-source software library developed by Yandex. It provides a gradient boosting framework which among other features attempts to solve for categorical features using a permutation driven alternative compared to the classical algorithm. [7] It works on Linux, Windows, macOS, and is available in Python, [8] R, [9 ...

  6. Gradient boosting - Wikipedia

    en.wikipedia.org/wiki/Gradient_boosting

    Gradient boosting is a machine learning technique based on boosting in a functional space, where the target is pseudo-residuals instead of residuals as in traditional boosting. It gives a prediction model in the form of an ensemble of weak prediction models, i.e., models that make very few assumptions about the data, which are typically simple ...

  7. Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Receiver_operating...

    A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model (can be used for multi class classification as well) at varying threshold values. The ROC curve is the plot of the true positive rate (TPR) against the false positive rate (FPR) at each threshold setting.

  8. Mortgage prequalification vs. preapproval: How to time these ...

    www.aol.com/finance/mortgage-prequalification-vs...

    Bolsters your position. A preapproval letter boosts your ability to bargain and can make your offer stand out among the crowd. Establishes your budget. Preapproval provides realistic and lender ...

  9. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]). The library is cross-platform and licensed as free and open-source software under Apache License 2.