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**Superclasses: **

Feature selection for regression using neighborhood component analysis (NCA)

`FeatureSelectionNCARegression`

contains the
data, fitting information, feature weights, and other model parameters
of a neighborhood component analysis (NCA) model. `fsrnca`

learns the feature weights using
a diagonal adaptation of NCA and returns an instance of `FeatureSelectionNCARegression`

object.
The function achieves feature selection by regularizing the feature
weights.

Create a `FeatureSelectionNCAClassification`

object using `fsrnca`

.

loss | Evaluate accuracy of learned feature weights on test data |

predict | Predict responses using neighborhood component analysis (NCA) regression model |

refit | Refit neighborhood component analysis (NCA) model for regression |

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