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R^2 = 1 - \frac{MSEMSD(x, \hat x)}{MSEMSD(x, \bar x)} = 1 - \frac{\sum_i (x_i -\hat x_i)}{\sum_i (x_i -\bar x)} |
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| observed variable represented by a discrete data set of numerical samples | ||||||||||||||||
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| predictor of variable with the same number of samples | ||||||||||||||||
| mean value of the variable
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| mean square error between deviation between a variable | ||||||||||||||||
| mean square errordeviation between a variable |
It is similar to to Mean Square Error Deviation (MSEMSD) but quantifies the model prediction efficiency in normalized way which sometimes is more suitable for computations.
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