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» Classifying n-back EEG data using entropy and mutual informa...
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JMLR
2010
185views more  JMLR 2010»
13 years 17 days ago
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...
Franz Pernkopf, Jeff A. Bilmes
KDD
2002
ACM
126views Data Mining» more  KDD 2002»
14 years 6 months ago
Integrating feature and instance selection for text classification
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Dimitris Fragoudis, Dimitris Meretakis, Spiros Lik...
ECIR
2009
Springer
13 years 3 months ago
Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis
Abstract. In the community of sentiment analysis, supervised learning techniques have been shown to perform very well. When transferred to another domain, however, a supervised sen...
Songbo Tan, Xueqi Cheng, Yuefen Wang, Hongbo Xu
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 7 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
SSWMC
2004
13 years 7 months ago
Universal image steganalysis using rate-distortion curves
The goal of image steganography is to embed information in a cover image using modifications that are undetectable. In actual practice, however, most techniques produce stego imag...
Mehmet Utku Celik, Gaurav Sharma, A. Murat Tekalp