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» Optimal feature selection for support vector machines
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KDD
2006
ACM
170views Data Mining» more  KDD 2006»
14 years 8 months ago
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers
This paper describes a novel classification method for computer aided detection (CAD) that identifies structures of interest from medical images. CAD problems are challenging larg...
Jinbo Bi, Senthil Periaswamy, Kazunori Okada, Tosh...
IJCNN
2008
IEEE
14 years 2 months ago
Ranking and selecting clustering algorithms using a meta-learning approach
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Marcílio Carlos Pereira de Souto, Ricardo B...
ICIP
2008
IEEE
14 years 9 months ago
Emotional valence categorization using holistic image features
Can a machine learn to perceive emotions as evoked by an artwork? Here we propose an emotion categorization system, trained by ground truth from psychology studies. The training d...
Victoria Yanulevskaya, Jan van Gemert, Katharina R...
ICPR
2002
IEEE
14 years 9 months ago
Feature Selection for Pose Invariant Face Recognition
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
Berk Gökberk, Ethem Alpaydin, Lale Akarun
ECML
2007
Springer
14 years 2 months ago
Optimizing Feature Sets for Structured Data
Choosing a suitable feature representation for structured data is a non-trivial task due to the vast number of potential candidates. Ideally, one would like to pick a small, but in...
Ulrich Rückert, Stefan Kramer