5092 search results - page 159 / 1019 » Clustering the Feature Space |
186
Voted
MM
2005
ACM
16 years 18 days ago
2005
ACM
We consider the problem of image representation and clustering. Traditionally, an n1 × n2 image is represented by a vector in the Euclidean space Rn1×n2 . Some learning algorith...
194
Voted
COMPGEOM
2009
ACM
15 years 11 months ago
2009
ACM
The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice....
189
Voted
ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
175
Voted
LWA
2007
15 years 8 months ago
2007
Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
212
click to vote
NN
2008
Springer
15 years 6 months ago
2008
Springer
This paper introduces an approach called Clustering and Co-evolution to Construct Neural Network Ensembles (CONE). This approach creates neural network ensembles in an innovative ...