Main Content

**Package: **classreg.learning.regr

Compact Gaussian process regression model class

`CompactRegressionGP`

is a compact Gaussian process regression (GPR)
model. The compact model consumes less memory than a full model, because it does not
include the data used for training the GPR model.

Because the compact model does not include the training data, you cannot perform some
tasks, such as cross-validation, using the compact model. However, you can use the
compact model for making predictions or calculate regression loss for new data (use
`predict`

and `loss`

).

Create a `CompactRegressionGP`

object from a full `RegressionGP`

model object by using `compact`

.

`lime` | Local interpretable model-agnostic explanations (LIME) |

`loss` | Regression error for Gaussian process regression model |

`partialDependence` | Compute partial dependence |

`plotPartialDependence` | Create partial dependence plot (PDP) and individual conditional expectation (ICE) plots |

`predict` | Predict response of Gaussian process regression model |

`shapley` | Shapley values |

Value. To learn how value classes affect copy operations, see Copying Objects.