Feature selection for classification using neighborhood component analysis (NCA)
FeatureSelectionNCAClassification
object contains the data, fitting
information, feature weights, and other parameters of a neighborhood component analysis
(NCA) model. fscnca
learns the feature weights using a
diagonal adaptation of NCA and returns an instance of a
FeatureSelectionNCAClassification
object. The function achieves
feature selection by regularizing the feature weights.
Create a FeatureSelectionNCAClassification
object using fscnca
.
loss | Evaluate accuracy of learned feature weights on test data |
predict | Predict responses using neighborhood component analysis (NCA) classifier |
refit | Refit neighborhood component analysis (NCA) model for classification |
Value. To learn how value classes affect copy operations, see Copying Objects.