Mean Prediction Error Calculator

Mean Squared Prediction Error is the index used in the measurement of quality of a predictor. It measures the expected value of the squared difference between what the predictor predicts for a specific value and the true value. It is the inverse model of the explanatory power. It is also used in the process of cross validation of an estimated model. Give the slope, constant and X, Y values separated by commas to find Mean Squared Prediction Error using this mean prediction calculator.

Mean Squared Prediction Error Calculation

Mean Squared Prediction Error is the index used in the measurement of quality of a predictor. It measures the expected value of the squared difference between what the predictor predicts for a specific value and the true value. It is the inverse model of the explanatory power. It is also used in the process of cross validation of an estimated model. Give the slope, constant and X, Y values separated by commas to find Mean Squared Prediction Error using this mean prediction calculator.

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Formula:

μ = ( ∑ (y-y') ) / n Where, μ = Mean Prediction Error y = Data y' = Predicted Data n = Number of Data

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