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  2. Confusion matrix - Wikipedia

    en.wikipedia.org/wiki/Confusion_matrix

    Confusion matrix is not limited to binary classification and can be used in multi-class classifiers as well. The confusion matrices discussed above have only two conditions: positive and negative. For example, the table below summarizes communication of a whistled language between two speakers, with zero values omitted for clarity. [24]

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    For example, word2vec has been used to map a vector space of words in one language to a vector space constructed from another language. Relationships between translated words in both spaces can be used to assist with machine translation of new words.

  4. Evaluation of binary classifiers - Wikipedia

    en.wikipedia.org/wiki/Evaluation_of_binary...

    These can be arranged into a 2×2 contingency table (confusion matrix), conventionally with the test result on the vertical axis and the actual condition on the horizontal axis. These numbers can then be totaled, yielding both a grand total and marginal totals. Totaling the entire table, the number of true positives, false negatives, true ...

  5. XGBoost - Wikipedia

    en.wikipedia.org/wiki/XGBoost

    Soon after, the Python and R packages were built, and XGBoost now has package implementations for Java, Scala, Julia, Perl, and other languages. This brought the library to more developers and contributed to its popularity among the Kaggle community, where it has been used for a large number of competitions.

  6. Independent component analysis - Wikipedia

    en.wikipedia.org/wiki/Independent_component_analysis

    The unmixing matrix that maximizes equation is known as the MLE of the optimal unmixing matrix. It is common practice to use the log likelihood , because this is easier to evaluate. As the logarithm is a monotonic function, the W {\displaystyle \mathbf {W} } that maximizes the function L ( W ) {\displaystyle \mathbf {L(W)} } also maximizes its ...

  7. Phi coefficient - Wikipedia

    en.wikipedia.org/wiki/Phi_coefficient

    In statistics, the phi coefficient (or mean square contingency coefficient and denoted by φ or r φ) is a measure of association for two binary variables.. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975.

  8. Comparison of linear algebra libraries - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_linear...

    High-performance multi-threaded primitives for large sparse matrices. Support operations for iterative solvers: multiplication, triangular solve, scaling, matrix I/O, matrix rendering. Many variants: e.g.: symmetric, hermitian, complex, quadruple precision. oneMKL: Intel C, C++, Fortran 2003 2023.1 / 03.2023 Non-free Intel Simplified Software ...

  9. Caret (software) - Wikipedia

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

    CARET (Computerized Anatomical Reconstruction Toolkit) is a software application for the structural and functional analysis of the cerebral and cerebellar cortex. CARET is developed in the Van Essen Laboratory in the Department of Anatomy and Neurobiology at the Washington University School of Medicine in St. Louis, Missouri .