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Fast Clustering based on Kernel Density Estimation
Published on Oct 08, 200710039 Views
The Denclue algorithm employs a cluster model based on kernel density estimation. A cluster is defined by a local maximum of the estimated density function. Data points are assigned to clusters by
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Chapter list
Fast Clustering Based on Kernel Density Estimation 00:00
Overview00:29
Density-Based Clustering01:07
Kernel Density Estimation01:44
Denclue 1.0 Framework03:00
Problem of Constant Step Size04:01
New Hill Climbing Approach04:32
New Denclue 2.0 Hill Climbing05:11
New Hill Climbing Approach (a)05:19
New Denclue 2.0 Hill Climbing (a)05:31
Proof of Convergence pt 105:50
Proof of Convergence pt 207:15
Identification of Local Maxima07:58
Acceleration09:40
Experiments pt 111:29
Experiments pt 212:09
Experiments pt 312:33
Experiments pt 413:19
Conclusion14:22
Thank You for Your Attention!14:58
Experiments pt 4 (a)18:52