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The Smart Health paradigm has opened up immense possibilities for designing cyber-physical systems with integrated sensing and analysis for data-driven healthcare decision-making. Clinical motor-rehabilitation has traditionally tended to entail labor-intensive approaches with limited quantitative methods and numerous logistics deployment challenges. We believe such labor-intensive rehabilitation procedures...
An adaptive k-nearest neighbor algorithm (AdaNN) is brought forward in this paper to overcome the limitation of the traditional k-nearest neighbor algorithm (kNN) which usually identifies the same number of nearest neighbors for each test example. It is known that the value of k has crucial influence on the performance of the kNN algorithm, and our improved kNN algorithm focuses on finding out the...
The k-nearest neighbors classifier is simple and often results in good classification performance on problems with unknown and non-normal distributions. However, its selected nearest neighbors on noisy, sparse, or imbalanced data are often inconsistent with our intuition and in turn leads to the worse performance. This paper applies Gestalt visual perceptual laws to design a new KNN classifie r. It...
Collaborative filtering has been very successful in both research and applications. Current collaborative filtering based on clustering compute the whole set of items during the process of clustering or selecting nearest-neighbors, because the researchers believed if users have similar preferences on some of items, they will have the similar preferences on other items. But we think that users have...
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