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» Building Classifiers Using Bayesian Networks
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KDD
2003
ACM
148views Data Mining» more  KDD 2003»
16 years 1 days ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
ICDAR
2007
IEEE
15 years 6 months ago
A Shared Parts Model for Document Image Recognition
We address document image classification by visual appearance. An image is represented by a variable-length list of visually salient features. A hierarchical Bayesian network is ...
M. Das Gupta, P. Sarkar
CVPR
1999
IEEE
16 years 1 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
IJCAI
2007
15 years 1 months ago
Learning to Identify Unexpected Instances in the Test Set
Traditional classification involves building a classifier using labeled training examples from a set of predefined classes and then applying the classifier to classify test instan...
Xiaoli Li, Bing Liu, See-Kiong Ng
ICML
2008
IEEE
16 years 13 days ago
Classification using discriminative restricted Boltzmann machines
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
Hugo Larochelle, Yoshua Bengio