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  2. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).

  3. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

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

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

    Data from nine subjects collected using P300-based brain-computer interface for disabled subjects. Split into four sessions for each subject. MATLAB code given. 1,224 Text Classification 2008 [264] [265] U. Hoffman et al. Heart Disease Data Set Attributed of patients with and without heart disease.

  5. 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 ...

  6. Pseudo-R-squared - Wikipedia

    en.wikipedia.org/wiki/Pseudo-R-squared

    R 2 L is given by Cohen: [1] =. This is the most analogous index to the squared multiple correlations in linear regression. [3] It represents the proportional reduction in the deviance wherein the deviance is treated as a measure of variation analogous but not identical to the variance in linear regression analysis. [3]

  7. Evaluation measures (information retrieval) - Wikipedia

    en.wikipedia.org/wiki/Evaluation_measures...

    Cleverdon’s experiments established a number of key aspects required for IR evaluation: a test collection, a set of queries and a set of pre-determined relevant items which combined would determine precision and recall. Cleverdon's approach formed a blueprint for the successful Text Retrieval Conference series that began in 1992.

  8. Deming regression - Wikipedia

    en.wikipedia.org/wiki/Deming_regression

    In statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model that tries to find the line of best fit for a two-dimensional data set. It differs from the simple linear regression in that it accounts for errors in observations on both the x- and the y- axis.

  9. Iris flower data set - Wikipedia

    en.wikipedia.org/wiki/Iris_flower_data_set

    The iris data set is widely used as a beginner's dataset for machine learning purposes. The dataset is included in R base and Python in the machine learning library scikit-learn, so that users can access it without having to find a source for it. Several versions of the dataset have been published. [8]