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» Fuzzy Clustering of Series Using Quantile Autocovariances
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IDA
2003
Springer
13 years 10 months ago
Fuzzy Clustering Based Segmentation of Time-Series
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
János Abonyi, Balazs Feil, Sandor Z. N&eacu...
ENGL
2007
191views more  ENGL 2007»
13 years 4 months ago
Data Mining for extraction of fuzzy IF-THEN rules using Mamdani and Takagi-Sugeno-Kang FIS
— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...
NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 4 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
EUSFLAT
2009
163views Fuzzy Logic» more  EUSFLAT 2009»
13 years 2 months ago
A Fuzzy Set Approach to Ecological Knowledge Discovery
Besides the problem of searching for effective methods for extracting knowledge from large databases (KDD) there are some additional problems with handling ecological data, namely ...
Arkadiusz Salski
FSKD
2005
Springer
267views Fuzzy Logic» more  FSKD 2005»
13 years 10 months ago
Preventing Meaningless Stock Time Series Pattern Discovery by Changing Perceptually Important Point Detection
Discovery of interesting or frequently appearing time series patterns is one of the important tasks in various time series data mining applications. However, recent research critic...
Tak-Chung Fu, Fu-Lai Chung, Robert W. P. Luk, Chak...