Impact Parameter Analysis of Subspace Clustering
نویسندگان
چکیده
منابع مشابه
Subspace Clustering
Data structure analysis is an important basis of machine learning and data science, which is now widely used in computational visualization problems, e.g. facial recognition, image classification, and motion segmentation. In this project, I would like to deal with a set of small classification problems and use methods like PCA, spectral analysis, kmanifold, etc. By exploring different methods, ...
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To achieve an insightful clustering of multivariate data, we propose subspace K-means. Its central idea is to model the centroids and cluster residuals in reduced spaces, which allows for dealing with a wide range of cluster types and yields rich interpretations of the clusters. We review the existing related clustering methods, including deterministic, stochastic, and unsupervised learning app...
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ژورنال
عنوان ژورنال: International Journal of Distributed Sensor Networks
سال: 2015
ISSN: 1550-1477,1550-1477
DOI: 10.1155/2015/398452