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[HTML][HTML] Quadratic mutual information feature selection
D Sluga, U Lotrič - Entropy, 2017 - mdpi.com
We propose a novel feature selection method based on quadratic mutual information which
has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct …
has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct …
Hybrid sub-space detection technique for effective hyperspectral image classification
Subspace detection for hyperspectral images is getting more interest now days because of
the challenges of dealing with high dimensional feature space for reliable classification. The …
the challenges of dealing with high dimensional feature space for reliable classification. The …
Hybrid technique for classification of hyperspectral image using quadratic mutual information
Researchers have found profound interest in the field 'hyperspectral imaging'as it has
numerous applications. However, the center of motivation for this task has been the …
numerous applications. However, the center of motivation for this task has been the …
[PDF][PDF] Hybrid subspace detection based on spectral and spatial information for effective hyperspectral image classification
Subspace detection of remote sensing hyperspectral image data cube has become an
important area of research because of the challenges of dealing with high dimensional …
important area of research because of the challenges of dealing with high dimensional …
[PDF][PDF] Year of Publication: 2019
SZ Mishu, B Ahmed - 2019 - academia.edu
Subspace detection of remote sensing hyperspectral image data cube has become an
important area of research because of the challenges of dealing with high dimensional …
important area of research because of the challenges of dealing with high dimensional …
Iskanje odvisnosti v podatkih z metodami teorije informacij
D Sluga - 2017 - eprints.fri.uni-lj.si
The selection of features that are relevant for a classification or a regression problem is very
important in many domains which involve high-dimensional data. It improves the …
important in many domains which involve high-dimensional data. It improves the …