Adaptive Learning-Based k -Nearest Neighbor Classifiers With Resilience to Class Imbalance

The classification accuracy of a <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-nearest neighbor (<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>NN) classifier is largely depend...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 29; číslo 11; s. 5713 - 5725
Hlavní autori:	Mullick, Sankha Subhra, Datta, Shounak, Das, Swagatam
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.11.2018
Predmet:	<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k -nearest neighbor (<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k NN) Classification algorithms Clustering algorithms Heuristic learning imbalanced classification Learning systems parameter adaptation Resilience supervised learning Task analysis Training Tuning
ISSN:	2162-237X, 2162-2388
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