# CompactRegressionEnsemble

Compact regression ensemble

## Description

Compact version of a regression ensemble. The compact version does not include the data for training the regression ensemble. Therefore, you cannot perform some tasks with a compact regression ensemble, such as cross validation. Use a compact regression ensemble for making predictions (regressions) of new data.

## Creation

Create a `CompactRegressionEnsemble`

object from a full `RegressionEnsemble`

or `RegressionBaggedEnsemble`

model object by using `compact`

.

## Properties

## Object Functions

`gather` | Gather properties of Statistics and Machine Learning Toolbox object from GPU |

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

`loss` | Regression error for regression ensemble model |

`partialDependence` | Compute partial dependence |

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

`predict` | Predict responses using regression ensemble model |

`predictorImportance` | Estimates of predictor importance for regression ensemble of decision trees |

`removeLearners` | Remove members of compact regression ensemble |

`shapley` | Shapley values |

## Examples

## Tips

For a compact ensemble of regression trees, the `Trained`

property
of `ens`

stores a cell vector of `ens.NumTrained`

`CompactRegressionTree`

model objects. For a textual or graphical display of
tree * t* in the cell vector,
enter

view(ens.Trained{t})

## Extended Capabilities

## Version History

**Introduced in R2011a**

## See Also

`fitrensemble`

| `RegressionEnsemble`

| `RegressionBaggedEnsemble`

| `predict`

| `compact`

| `templateTree`

| `view`