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CAEPIA
2003
Springer
13 years 8 months ago
Rotation-Based Ensembles
A new method for ensemble generation is presented. It is based on grouping the attributes in dierent subgroups, and to apply, for each group, an axis rotation, using Principal Com...
Juan José Rodríguez, Carlos J. Alons...
DOCENG
2003
ACM
13 years 8 months ago
Accuracy improvement of automatic text classification based on feature transformation
In this paper, we describe a comparative study on techniques of feature transformation and classification to improve the accuracy of automatic text classification. The normalizati...
Guowei Zu, Wataru Ohyama, Tetsushi Wakabayashi, Fu...
ISNN
2004
Springer
13 years 9 months ago
Progressive Principal Component Analysis
Abstract. Principal Component Analysis (PCA) is a feature extraction approach directly based on a whole vector pattern and acquires a set of projections that can realize the best r...
Jun Liu, Songcan Chen, Zhi-Hua Zhou
IDEAL
2004
Springer
13 years 9 months ago
Dimensionality Reduction with Image Data
A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We pro...
Mónica Benito, Daniel Peña
ICIAR
2004
Springer
13 years 9 months ago
Visual Object Recognition Through One-Class Learning
Abstract. In this paper, several one-class classification methods are investigated in pixel space and PCA (Principal component Analysis) subspace having in mind the need of finding...
QingHua Wang, Luís Seabra Lopes, David M. J...
MM
2004
ACM
248views Multimedia» more  MM 2004»
13 years 9 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
TSD
2005
Springer
13 years 9 months ago
Mapping the Speech Signal onto Electromagnetic Articulography Trajectories Using Support Vector Regression
Abstract. We report work on the mapping between the speech signal and articulatory trajectories from the MOCHA database. Contrasting previous works that used Neural Networks for th...
Asterios Toutios, Konstantinos G. Margaritis
PAKDD
2005
ACM
164views Data Mining» more  PAKDD 2005»
13 years 9 months ago
Covariance and PCA for Categorical Variables
Covariances from categorical variables are defined using a regular simplex expression for categories. The method follows the variance definition by Gini, and it gives the covaria...
Hirotaka Niitsuma, Takashi Okada
IMC
2005
ACM
13 years 9 months ago
Network Anomography
Anomaly detection is a first and important step needed to respond to unexpected problems and to assure high performance and security in IP networks. We introduce a framework and ...
Yin Zhang, Zihui Ge, Albert G. Greenberg, Matthew ...
ICMCS
2005
IEEE
138views Multimedia» more  ICMCS 2005»
13 years 9 months ago
Overcomplete ICA-based Manmade Scene Classification
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
Matthew Boutell, Jiebo Luo