Nearest Class with Multiple Centroids (NCMC)

A distance metric learning algorithm for nearest centroids classification. It learns a transformation that optimizes the expected score of multiple centroid classification. The associated classifier establishes a variable number of centroids for each class via k-Means, and predicts the new labels according to the class of the nearest centroid. This classifier is also available in this package.

Watch the full NCMC documentation here. Watch also the NCMC Classifier documentation.

References

Thomas Mensink et al. “Metric learning for large scale image classification: Generalizing to new classes at near-zero cost”. In: Computer Vision–ECCV 2012. Springer, 2012, pages 488-501.