113 search results - page 2 / 23 » Locally adaptive metrics for clustering high dimensional dat... |
FSKD
2006
Springer
13 years 9 months ago
2006
Springer
Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional spac...
ICDM
2002
IEEE
13 years 10 months ago
2002
IEEE
The k-means algorithm with cosine similarity, also known as the spherical k-means algorithm, is a popular method for clustering document collections. However, spherical k-means ca...
VLDB
2000
ACM
13 years 9 months ago
2000
ACM
Many emerging application domains require database systems to support efficient access over highly multidimensional datasets. The current state-of-the-art technique to indexing hi...
APVIS
2010
13 years 3 months ago
2010
In this paper, we propose an approach of clustering data in parallel coordinates through interactive local operations. Different from many other methods in which clustering is glo...
NIPS
2004
13 years 6 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...