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» Feature selection based on the training set manipulation
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ICPR
2006
IEEE
16 years 5 months ago
Adaptive Feature Integration for Segmentation of 3D Data by Unsupervised Density Estimation
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
Marco Cristani, Umberto Castellani, Vittorio Murin...
IJCNN
2000
IEEE
15 years 9 months ago
Supervised Scaled Regression Clustering: An Alternative to Neural Networks
: This paper describes a rather novel method for the supervised training of regression systems that can be an alternative to feedforward Artificial Neural Networks (ANNs) trained w...
Mark J. Embrechts, Dirk Devogelaere, Marcel Rijcka...
COLING
2010
14 years 11 months ago
Sentiment Classification and Polarity Shifting
Polarity shifting marked by various linguistic structures has been a challenge to automatic sentiment classification. In this paper, we propose a machine learning approach to inco...
Shoushan Li, Sophia Yat Mei Lee, Ying Chen, Chu-Re...
ICPR
2008
IEEE
15 years 11 months ago
Optimal feature weighting for the continuous HMM
We propose new Continuous Hidden Markov Model (CHMM) structure that integrates feature weighting component. We assume that each feature vector could include different subsets of f...
Oualid Missaoui, Hichem Frigui
IJCV
2008
192views more  IJCV 2008»
15 years 4 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...