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Predict responses for training data using trained regression model

specifies options using one or more name-value arguments. For example,
`yFit`

= resubPredict(`Mdl`

,`Name,Value`

)`'IncludeInteractions',true`

specifies to include interaction terms in
computations for generalized additive models. This syntax applies only to generalized
additive models and Gaussian process regression models.

`[`

also returns the standard deviations and prediction intervals of the response variable,
evaluated at each observation in the predictor data `yFit`

,`ySD`

,`yInt`

] = resubPredict(___)`Mdl.X`

, using any of
the input argument combinations in the previous syntaxes. This syntax applies only to
generalized additive models for which `IsStandardDeviationFit`

is `true`

, and to Gaussian process
regression models for which the `PredictMethod`

is not
`'bcd'`

.

`resubPredict`

predicts responses according to the corresponding
`predict`

function of the object (`Mdl`

). For a
model-specific description, see the `predict`

function reference pages in
the following table.

Model | Regression Model Object (`Mdl` ) | `predict` Object Function |
---|---|---|

Gaussian process regression model | `RegressionGP` | `predict` |

Generalized additive model | `RegressionGAM` | `predict` |

Neural network model | `RegressionNeuralNetwork` | `predict` |

To compute the predicted responses for new predictor data, use the corresponding
`predict`

function of the object (`Mdl`

).