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» Fast Feature Selection Using Fractal Dimension
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TIP
2002
133views more  TIP 2002»
13 years 8 months ago
Wavelet-based rotational invariant roughness features for texture classification and segmentation
In this paper, we introduce a rotational invariant feature set for texture segmentation and classification, based on an extension of fractal dimension (FD) features. The FD extract...
Dimitrios Charalampidis, Takis Kasparis
BMCBI
2004
167views more  BMCBI 2004»
13 years 8 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
IJCAI
2007
13 years 9 months ago
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...
ICML
2003
IEEE
14 years 9 months ago
Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution
Feature selection, as a preprocessing step to machine learning, has been effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improvin...
Lei Yu, Huan Liu
IEAAIE
2003
Springer
14 years 1 months ago
Fast Feature Selection by Means of Projections
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simple...
Roberto Ruiz, José Cristóbal Riquelm...