نتایج جستجو برای: k nn

تعداد نتایج: 385892  

2011
Shailendra Kumar Shrivastava Pradeep Mewada

The k-nearest neighbor (k-NN) is one of the most popular algorithms used for classification in various fields of pattern recognition & data mining problems. In k-nearest neighbor classification, the result of a new instance query is classified based on the majority of k-nearest neighbors. Recently researchers have begun paying attention to combining a set of individual k-NN classifiers, each us...

1994
David W. Aha Steven L. Salzberg

This paper examines the hypothesis that local weighted variants of k-nearest neighbor algorithms can support dynamic control tasks. We evaluated several k-nearest neighbor (k-NN) algorithms on the simulated learning task of catching a ying ball. Previously, local regression algorithms have been advocated for this class of problems. These algorithms, which are variants of k-NN, base their predic...

Journal: :Journal of Research and Practice in Information Technology 2004
Andrew Beng Jin Teoh Salina Abdul Samad Aini Hussain

Identity verification systems that use a mono modal biometrics always have to contend with sensor noise and limitations of feature extractor and matching. However combining information from different biometrics modalities may well provide higher and more consistent performance levels. A robust yet simple scheme can fuse the decisions produced by the individual biometric experts. In this paper, ...

1996
Jorma Laaksonen Erkki Oja

The nearest neighbor (NN) classiiers, especially the k-NN algorithm, are among the simplest and yet most eecient classiication rules and are widely used in practice. We introduce three adaptation rules that can be used in iterative training of a k-NN classiier. This is a novel approach both from the statistical pattern recognition and the supervised neural network learning points of view. The s...

2008
A. Valcarce

We calculate the doublet and quartet neutron-deuteron scattering lengths using a nonlocal nucleon-nucleon interaction fully derived from quark-quark interactions. We use as input the NN S0 and S1D1 partial waves. Our result for the quartet scattering length agrees well with the experimental value while the result for the doublet scattering length does not. However, if we take the result for the...

Journal: :International Journal of Advanced Trends in Computer Science and Engineering 2020

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