Goodness of Fit
Goodness of fit, classification, prediction; computes various goodness of fit indices based on a variable containing observed values or classification, and one or more variables containing predicted values or classifications. Both continuous variables (for regression-type problems) and categorical variables (for classification problems) can be analyzed. Various goodness of fit measures are available for classification and regression-type problems.
Continuous
Element Name | Description |
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Least squares deviation | Specifies whether to calculate the least squares deviation (LSD) goodness-of-fit measure. |
Average deviation | Specifies whether to calculate the average deviation goodness-of-fit measure. |
Relative squared error | Specifies whether to calculate the relative squared error goodness-of-fit measure; note that all observed values in this case must be greater than zero. |
Relative absolute error | Specifies whether to calculate the relative absolute error goodness-of-fit measure; note that all observed values in this case must be greater than zero. |
Correlation coefficient | Specifies whether to calculate the correlation coefficient goodness-of-fit measure. |
Categorical
Element Name | Description |
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Chi-squared test | Specifies whether to calculate the Chi-squared test goodness-of-fit measure. |
G-squared test | Specifies whether to calculate the G-squared test (maximum likelihood Chi-square) goodness-of-fit measure. |
Percent disagreement | Specifies whether to calculate the percent disagreement goodness-of-fit measure. |
Quadratic loss function | Specifies whether to calculate the quadratic loss function goodness-of-fit measure. |
Information loss function | Specifies whether to calculate the information loss function goodness-of-fit measure. |
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