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SMC
2010
IEEE
132views Control Systems» more  SMC 2010»
13 years 6 months ago
Selection of SIFT feature points for scene description in robot vision
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Yuya Utsumi, Masahiro Tsukada, Hirokazu Madokoro, ...
ICPR
2008
IEEE
14 years 2 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
CORR
2008
Springer
159views Education» more  CORR 2008»
13 years 8 months ago
Face Detection Using Adaboosted SVM-Based Component Classifier
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,...
TKDE
2008
123views more  TKDE 2008»
13 years 8 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
ICONIP
2007
13 years 9 months ago
Using Generalization Error Bounds to Train the Set Covering Machine
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
Zakria Hussain, John Shawe-Taylor