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  2. XLfit - Wikipedia

    en.wikipedia.org/wiki/XLfit

    XLfit is a Microsoft Excel add-in that can perform regression analysis, curve fitting, and statistical analysis. It is approved by the UK National Physical Laboratory and the US National Institute of Standards and Technology [1] XLfit can generate 2D and 3D graphs and analyze data sets. XLfit can also analyse the statistical data.

  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. Iterative proportional fitting - Wikipedia

    en.wikipedia.org/wiki/Iterative_proportional_fitting

    The iterative proportional fitting procedure (IPF or IPFP, also known as biproportional fitting or biproportion in statistics or economics (input-output analysis, etc.), RAS algorithm [1] in economics, raking in survey statistics, and matrix scaling in computer science) is the operation of finding the fitted matrix which is the closest to an initial matrix but with the row and column totals of ...

  5. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...

  6. Goodness of fit - Wikipedia

    en.wikipedia.org/wiki/Goodness_of_fit

    The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question.

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  8. Statistical graphics - Wikipedia

    en.wikipedia.org/wiki/Statistical_graphics

    They can also provide insight into a data set to help with testing assumptions, model selection and regression model validation, estimator selection, relationship identification, factor effect determination, and outlier detection. In addition, the choice of appropriate statistical graphics can provide a convincing means of communicating the ...

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