Literature DB >> 26479827

N3 and BNN: Two New Similarity Based Classification Methods in Comparison with Other Classifiers.

Roberto Todeschini1, Davide Ballabio1, Matteo Cassotti1, Viviana Consonni1.   

Abstract

Two novel classification methods, called N3 (N-nearest neighbors) and BNN (binned nearest neighbors), are proposed. Both methods are inspired by the principles of the K-nearest neighbors (KNN) method, being both based on object pairwise similarities. Their performance was evaluated in comparison with nine well-known classification methods. In order to obtain reliable statistics, several comparisons were performed using 32 different literature data sets, which differ for number of objects, variables and classes. Results highlighted that N3 on average behaves as the most efficient classification method with similar performance to support vector machine based on radial basis function kernel (SVM/RBF). The method BNN showed on average higher performance than the classical K-nearest neighbors method.

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Year:  2015        PMID: 26479827     DOI: 10.1021/acs.jcim.5b00326

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  4 in total

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Journal:  Environ Health Perspect       Date:  2021-04-30       Impact factor: 9.031

2.  A QSTR-Based Expert System to Predict Sweetness of Molecules.

Authors:  Cristian Rojas; Roberto Todeschini; Davide Ballabio; Andrea Mauri; Viviana Consonni; Piercosimo Tripaldi; Francesca Grisoni
Journal:  Front Chem       Date:  2017-07-25       Impact factor: 5.221

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  4 in total

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