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» A simple method of forecasting based on fuzzy time series
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BMCBI
2006
169views more  BMCBI 2006»
13 years 7 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
KDD
1998
ACM
141views Data Mining» more  KDD 1998»
13 years 12 months ago
Rule Discovery from Time Series
We consider the problem of nding rules relating patterns in a time series to other patterns in that series, or patterns in one series to patterns in another series. A simple examp...
Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Ren...
ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
14 years 29 days ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
DKE
2007
153views more  DKE 2007»
13 years 7 months ago
Adaptive similarity search in streaming time series with sliding windows
The challenge in a database of evolving time series is to provide efficient algorithms and access methods for query processing, taking into consideration the fact that the databas...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...
PAKDD
2007
ACM
224views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Graph Nodes Clustering Based on the Commute-Time Kernel
This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel...
Luh Yen, François Fouss, Christine Decaeste...