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» Evaluating algorithms that learn from data streams
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ICML
2008
IEEE
15 years 11 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
TFS
2008
230views more  TFS 2008»
14 years 10 months ago
SGERD: A Steady-State Genetic Algorithm for Extracting Fuzzy Classification Rules From Data
Abstract--This paper considers the automatic design of fuzzyrule-based classification systems from labeled data. The performance of classifiers and the interpretability of generate...
Eghbal G. Mansoori, Mansoor J. Zolghadri, Seraj D....
85
Voted
HIS
2008
14 years 11 months ago
Artificial Data Sets Based on Knowledge Generators: Analysis of Learning Algorithms Efficiency
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...
SIGMOD
2010
ACM
259views Database» more  SIGMOD 2010»
15 years 2 months ago
PODS: a new model and processing algorithms for uncertain data streams
Uncertain data streams, where data is incomplete, imprecise, and even misleading, have been observed in many environments. Feeding such data streams to existing stream systems pro...
Thanh T. L. Tran, Liping Peng, Boduo Li, Yanlei Di...
ICDE
2012
IEEE
237views Database» more  ICDE 2012»
13 years 16 days ago
On Discovery of Traveling Companions from Streaming Trajectories
— The advance of object tracking technologies leads to huge volumes of spatio-temporal data collected in the form of trajectory data stream. In this study, we investigate the pro...
Lu An Tang, Yu Zheng, Jing Yuan, Jiawei Han, Alice...