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» Time series clustering based on forecast densities
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DATAMINE
2006
224views more  DATAMINE 2006»
14 years 9 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
IJON
2007
106views more  IJON 2007»
14 years 9 months ago
Forecasting the CATS benchmark with the Double Vector Quantization method
The Double Vector Quantization (DVQ) method, a long-term forecasting method based on the self-organizing maps algorithm, has been used to predict the 100 missing values of the CAT...
Geoffroy Simon, John Aldo Lee, Marie Cottrell, Mic...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
14 years 11 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
FPGA
1999
ACM
115views FPGA» more  FPGA 1999»
15 years 2 months ago
Using Cluster-Based Logic Blocks and Timing-Driven Packing to Improve FPGA Speed and Density
In this paper, we investigate the speed and area-efficiency of FPGAs employing “logic clusters” containing multiple LUTs and registers as their logic block. We introduce a ne...
Alexander Marquardt, Vaughn Betz, Jonathan Rose
AUSDM
2007
Springer
110views Data Mining» more  AUSDM 2007»
15 years 3 months ago
Useful Clustering Outcomes from Meaningful Time Series Clustering
Clustering time series data using the popular subsequence (STS) technique has been widely used in the data mining and wider communities. Recently the conclusion was made that it i...
Jason Chen