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In conjunction with modified SVM classifier, we use Fishers method for feature selection.
Test provided, allowed to identify the best method for feature combination.
A method for feature subset selection has also been introduced too.
Finally, adjacent section contours were matched directly with Fourier-Mellin curve matching method for feature extraction.
To address this issue, in this paper we propose a novel Partial Differential Equation (PDE) based method for feature learning.
We propose a method for feature extraction from clinical color images, with application in classification of skin lesions.
Similar(17)
Statistical adaptation method is a classical method for feature-based case adaptation (FCA) because of its domain-independent and easily to be implemented, but with low adaptation accuracy.
We propose generic information-theoretic methods for feature space slicing and for determining the appropriate number of subspaces for any statistical ADS.
The proposed algorithms are compared with some related methods for feature selection on some open gene expression datasets and UCI datasets.
The proposed methods for feature extraction, modeling and learning, increased the phoneme recognition rates in 28.13%, with better convergence than models based on Gaussian mixtures.
In the present study, we used forward selection and backward elimination methods for feature selection.
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