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Mostrando ítems 1-5 de 5
Artículo
On the evolutionary weighting of neighbours and features in the k-nearest neighbour rule
(Elsevier, 2019)
This paper presents an evolutionary method for modifying the behaviour of the k-Nearest-Neighbour clas sifier (kNN) called Simultaneous Weighting of Attributes and Neighbours (SWAN). Unlike other weighting methods, SWAN ...
Artículo
EVOR-STACK: A label-dependent evolutive stacking on remote sensing data fusion
(Elsevier, 2012)
Land use and land covers (LULC) maps are remote sensing products that are used to classify areas into different landscapes. Data fusion for remote sensing is becoming an important tool to improve classical approaches. ...
Artículo
On the evolutionary optimization of k-NN by label-dependent feature weighting
(Elsevier, 2012)
Different approaches of feature weighting and k-value selection to improve the nearest neighbour technique can be found in the literature. In this work, we show an evolutionary approach called k-Label Dependent Evolutionary ...
Artículo
An evolutionary voting for k-nearest neighbours
(Elsevier, 2016)
This work presents an evolutionary approach to modify the voting system of the k-nearest neighbours (kNN) rule we called EvoNN. Our approach results in a real-valued vector which provides the optimal relative con-tribution ...
Artículo
An evolutionary-weighted majority voting and support vector machines applied to contextual classification of LiDAR and imagery data fusion
(Elsevier, 2015)
Data classification is a critical step to convert remotely sensed data into thematic information. Environmental researchers have recently maximized the synergy between passive sensors and LiDAR (Light Detection and Ranging) ...