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Compact neural network model for classification

`CompactClassificationNeuralNetwork`

is a compact version of a
`ClassificationNeuralNetwork`

model object. The compact model does not include the
data used for training the classifier. Therefore, you cannot perform some tasks, such as
cross-validation, using the compact model. Use a compact model for tasks such as predicting
the labels of new data.

Create a `CompactClassificationNeuralNetwork`

object from a full `ClassificationNeuralNetwork`

model object by using `compact`

.

`compareHoldout` | Compare accuracies of two classification models using new data |

`edge` | Classification edge for neural network classifier |

`loss` | Classification loss for neural network classifier |

`margin` | Classification margins for neural network classifier |

`partialDependence` | Compute partial dependence |

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

`predict` | Classify observations using neural network classifier |

`ClassificationNeuralNetwork`

| `ClassificationPartitionedModel`

| `compact`

| `edge`

| `fitcnet`

| `loss`

| `margin`

| `predict`