Feature Weighting in k-Means Clustering.

Data sets with multiple, heterogeneous feature spaces occur frequently. We present an abstract framework for integrating multiple feature spaces in the k-means clustering algorithm. Our main ideas are (i) to represent each data object as a tuple of multiple feature vectors, (ii) to assign a suitable...

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Xuất bản năm:	Machine learning. 52, 3 (2003).
Tác giả chính:	Modha, Dharmendra S.
Định dạng:	Bài viết
Ngôn ngữ:	English
Những chủ đề:	Clustering. Convexity. Convex k-means algorithm. Feature combination. Feature selection. Fisher's discriminant analysis. Text mining. Unsupervised learning.