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  2. Naive Bayes classifier - Wikipedia

    en.wikipedia.org/wiki/Naive_Bayes_classifier

    In the statistics literature, naive Bayes models are known under a variety of names, including simple Bayes and independence Bayes. [3] All these names reference the use of Bayes' theorem in the classifier's decision rule, but naive Bayes is not (necessarily) a Bayesian method.

  3. Multiclass classification - Wikipedia

    en.wikipedia.org/wiki/Multiclass_classification

    This section discusses strategies of extending the existing binary classifiers to solve multi-class classification problems. Several algorithms have been developed based on neural networks, decision trees, k-nearest neighbors, naive Bayes, support vector machines and extreme learning machines to address multi-class classification problems ...

  4. mlpack - Wikipedia

    en.wikipedia.org/wiki/Mlpack

    mlpack is a free, open-source and header-only software library for machine learning and artificial intelligence written in C++, built on top of the Armadillo library and the ensmallen numerical optimization library.

  5. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    scikit-learn (a free and open-source machine learning library for the Python programming language). Weka (a free and open-source data-mining suite, contains many decision tree algorithms), Notable commercial software: MATLAB, Microsoft SQL Server, and; RapidMiner, SAS Enterprise Miner, IBM SPSS Modeler,

  6. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...

  7. 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 ...

  8. Bayes error rate - Wikipedia

    en.wikipedia.org/wiki/Bayes_error_rate

    Naive Bayes classifier; References This page was last edited on 17 December 2024, at 03:38 (UTC). Text is available under the ... Code of Conduct; Developers;

  9. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/wiki/Multinomial_logistic...

    In particular, learning in a naive Bayes classifier is a simple matter of counting up the number of co-occurrences of features and classes, while in a maximum entropy classifier the weights, which are typically maximized using maximum a posteriori (MAP) estimation, must be learned using an iterative procedure; see #Estimating the coefficients.