Sciweavers

ICPR
2008
IEEE
13 years 11 months ago
Spam filtering with several novel bayesian classifiers
In this paper, we report our work on spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Loca...
Chuanliang Chen, Yingjie Tian, Chunhua Zhang
MLDM
2009
Springer
13 years 11 months ago
A Two-fold PCA-Approach for Inter-Individual Recognition of Emotions in Natural Walking
This paper describes recognition of emotions of an unkown person during natural walking. As gait data is redundant, high dimensional and variable, effective feature extraction is ...
Michelle Karg, Robert Jenke, Kolja Kühnlenz, ...
KDD
2007
ACM
139views Data Mining» more  KDD 2007»
14 years 5 months ago
Raising the baseline for high-precision text classifiers
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
Aleksander Kolcz, Wen-tau Yih
KDD
2008
ACM
132views Data Mining» more  KDD 2008»
14 years 5 months ago
Partitioned logistic regression for spam filtering
Naive Bayes and logistic regression perform well in different regimes. While the former is a very simple generative model which is efficient to train and performs well empirically...
Ming-wei Chang, Wen-tau Yih, Christopher Meek
WWW
2009
ACM
14 years 5 months ago
Web-scale classification with naive bayes
Traditional Naive Bayes Classifier performs miserably on web-scale taxonomies. In this paper, we investigate the reasons behind such bad performance. We discover that the low perf...
Congle Zhang, Gui-Rong Xue, Yong Yu, Hongyuan Zha
ICML
2005
IEEE
14 years 5 months ago
Augmenting naive Bayes for ranking
Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
Harry Zhang, Liangxiao Jiang, Jiang Su
CVPR
2003
IEEE
14 years 7 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...