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» The Laplace-Jaynes approach to induction
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ICIP
2009
IEEE
14 years 8 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
98
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AI
2011
Springer
14 years 6 months ago
Learning qualitative models from numerical data
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Dem...
107
Voted
JCIT
2010
190views more  JCIT 2010»
14 years 5 months ago
Application of Feature Extraction Method in Customer Churn Prediction Based on Random Forest and Transduction
With the development of telecom business, customer churn prediction becomes more and more important. An outstanding issue in customer churn prediction is high dimensional problem....
Yihui Qiu, Hong Li
ILP
2000
Springer
15 years 2 months ago
Learning First Order Logic Time Series Classifiers
A method for learning multivariate time series classifiers by inductive logic programming is presented. Two types of background predicate that are suited for this task are introduc...
Juan José Rodríguez, Carlos J. Alons...
ENTCS
2008
73views more  ENTCS 2008»
14 years 11 months ago
Invariants for Non-Hierarchical Object Structures
We present a Hoare-style specification and verification approach for invariants in sequential OO programs. It allows invariants over nonhierarchical object structures, in which upd...
Ronald Middelkoop, Cornelis Huizing, Ruurd Kuiper,...