Regression Metrics

# Regression Metrics API Reference

## Functions

``FNorm( X )``

Calculates the Froebinius norm of matrix X.

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``MAE( y, yhat )``

Calculates Mean Average Error from vectors `Y` and `YHat`

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``MAPE( y, yhat )``

Calculates Mean Average Percent Error from vectors `Y` and `YHat`

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``ME( y, yhat )``

Calculates Mean Error from vectors `Y` and `YHat`.

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``MSE( y, yhat )``

Calculates Mean Squared Error from vectors `Y` and `YHat`

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``PearsonCorrelationCoefficient( y, yhat )``

Calculates The Pearson Correlation Coefficient from vectors `Y` and `YHat`

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``PercentRMSE( y, yhat; aspercent = true )``

Calculates Percent Root Mean Squared Error from vectors `Y` and `YHat`

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``RMSE( y, yhat )``

Calculates Root Mean Squared Error from vectors `Y` and `YHat`

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``RSquare( y, yhat )``

Calculates R^2 from `Y` and `YHat`

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``SSE( y, yhat )``

Calculates Sum of Squared Errors from vectors `Y` and `YHat`

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``SSReg( y, yhat )``

Calculates Sum of Squared Deviations due to Regression from vectors `Y` and `YHat`

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``SSRes( y, yhat )``

Calculates Sum of Squared Residuals from vectors `Y` and `YHat`

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``SSTotal( y, yhat )``

Calculates Total Sum of Squared Deviations from vectors `Y` and `YHat`

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