Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning

We extend soft nearest neighbor classification to fuzzy classification with adaptive class labels. The adaptation follows a gradient descent on a cost function. Further, it is applicable for general distance measures, in particular task specific choices and relevance learning for metric adaptation can be done. The performance of the algorithm is shown on synthetic as well as on real life data taken from proteomic research.