For classification of time series, the simple 1-nearest neighbor (1NN) classifier in combination with an elastic distance measure such as Dynamic Time Warping (DTW) distance is considered superior in terms of classification accuracy to many other more elaborate methods, including k-nearest neighbor (kNN) with neighborhood size k > 1. In this paper we revisit this apparently peculiar relationshi...

This paper is concerned with the impact of hubness, a general problem of machine learning in high-dimensional spaces, on a real-world music recommendation system based on visualisation of a k-nearest neighbour (knn) graph. Due to a problem of measuring distances in high dimensions, hub objects are recommended over and over again while anti-hubs are nonexistent in recommendation lists, resulting...

Lead-free (K0.5Na0.5)NbO3-LiNbO3 (KNN-LN) and (K0.5Na0.5)NbO3-LiTaO3 (KNN-LT) ferroelectric single crystals, with the dimensions of 11  11  5 mm and 5  5  3 mm, were grown successfully using the top-seeded solution growth (TSSG) method, respectively. The crystal structures were analyzed by means of X-ray diffraction, showing orthorhombic symmetry for KNN-LN single crystals and coexistence o...

Collaborative filtering has been very successful in both research and E-commence applications. One of the most popular collaborative filtering algorithms is the k-Nearest Neighbor (KNN) method, which finds k nearest neighbors for a given user to predict his interests. Previous research on KNN algorithm usually suffers from the data sparseness problem, because the quantity of items users voted i...

Nonparametric estimation of mutual information is used in a wide range of scientific problems to quantify dependence between variables. The k-nearest neighbor (knn) methods are consistent, and therefore expected to work well for a large sample size. These methods use geometrically regular local volume elements. This practice allows maximum localization of the volume elements, but can also induc...

Condition monitoring systems for prognostics and diagnostics can enable large and complex systems to be operated more safely, at a lower cost and have a longer lifetime than is possible without them. AURA Alert is a condition monitoring system that uses a fast approximate k Nearest Neighbour (kNN) search of a timeseries database containing known system states to identify anomalous system behavi...