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

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

    Spoken letter names. Features extracted from sounds. 7797 Text Classification 1994 [126] [127] R. Cole et al. Japanese Vowels Dataset Nine male speakers uttered two Japanese vowels successively. Applied 12-degree linear prediction analysis to it to obtain a discrete-time series with 12 cepstrum coefficients. 640 Text Classification 1999 [128] [129]

  3. Krippendorff's alpha - Wikipedia

    en.wikipedia.org/wiki/Krippendorff's_alpha

    Krippendorff's alpha coefficient, [1] named after academic Klaus Krippendorff, is a statistical measure of the agreement achieved when coding a set of units of analysis.. Since the 1970s, alpha has been used in content analysis where textual units are categorized by trained readers, in counseling and survey research where experts code open-ended interview data into analyzable terms, in ...

  4. Linear discriminant analysis - Wikipedia

    en.wikipedia.org/wiki/Linear_discriminant_analysis

    Standardized Coefficients: Each predictor's weight in the linear combination that is the discriminant function. Like in a regression equation, these coefficients are partial (i.e., corrected for the other predictors). Indicates the unique contribution of each predictor in predicting group assignment.

  5. 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.

  6. 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 ...

  7. Lasso (statistics) - Wikipedia

    en.wikipedia.org/wiki/Lasso_(statistics)

    In statistics and machine learning, lasso (least absolute shrinkage and selection operator; also Lasso or LASSO) is a regression analysis method that performs both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the resulting statistical model.

  8. Go Beyond The Basic Sandwich This Year—Here Are Our Most ...

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    Get the Thanksgiving Leftover Tacos recipe. PHOTO: ANDREW BUI; FOOD STYLING: Taylor Ann SPENCER. Kalimotxo Cola Punch. The last few months of the year mean it's time to party, and what better way ...

  9. Nash–Sutcliffe model efficiency coefficient - Wikipedia

    en.wikipedia.org/wiki/Nash–Sutcliffe_model...

    The Nash–Sutcliffe coefficient masks important behaviors that if re-cast can aid in the interpretation of the different sources of model behavior in terms of bias, random, and other components. [11] The alternate Kling–Gupta efficiency is intended to improve upon NSE by incorporating bias and variance terms. [12]