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» Predictive Learning Models for Concept Drift
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DIS
2004
Springer
14 years 1 months ago
Mining Noisy Data Streams via a Discriminative Model
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
Fang Chu, Yizhou Wang, Carlo Zaniolo
BMCBI
2006
150views more  BMCBI 2006»
13 years 7 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky
AAAI
2011
12 years 7 months ago
Temporal Dynamics of User Interests in Tagging Systems
Collaborative tagging systems are now deployed extensively to help users share and organize resources. Tag prediction and recommendation systems generally model user behavior as r...
Dawei Yin, Liangjie Hong, Zhenzhen Xue, Brian D. D...
AIA
2007
13 years 9 months ago
A framework for generating data to simulate changing environments
A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practi...
Anand M. Narasimhamurthy, Ludmila I. Kuncheva
ICMI
2010
Springer
141views Biometrics» more  ICMI 2010»
13 years 5 months ago
Learning and evaluating response prediction models using parallel listener consensus
Traditionally listener response prediction models are learned from pre-recorded dyadic interactions. Because of individual differences in behavior, these recordings do not capture...
Iwan de Kok, Derya Ozkan, Dirk Heylen, Louis-Phili...