Supervised discretization for decluttering classification models-Reference-Cited by-同舟云学术

Supervised discretization for decluttering classification models

Published:2023 Issue:23 Volume:148 Page:6097-6108
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Jordan James A.¹^ORCID,Celani Caelin P.²^ORCID,Ketterer Michael³,Lavine Barry K.⁴^ORCID,Booksh K. S.²^ORCID

Affiliation:

1. United States Geological Survey, Reston, VA, USA

2. University of Delaware, Department of Chemistry and Biochemistry, Newark, DE, USA

3. Northern Arizona University, Department of Chemistry and Biochemistry, Flagstaff, AZ, USA

4. Oklahoma State University, Department of Chemistry, Stillwater, OK, USA

Abstract

Supervised discretization ‘declutters’ chemical sensor data to sharpen the observed differences between classes and improve multivariate classification models.

Funder

National Science Foundation

Publisher

Royal Society of Chemistry (RSC)

Subject

Electrochemistry,Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/AN/D3AN00770G

Reference29 articles.

1. Y.Yang , G. I.Webb and X.Wu , Discretization Methods , in Data Mining and Knowledge Discovery Handbook , Springer US , 2009 , pp. 101–116 . 10.1007/978-0-387-09823-4_6

2. Discretization as the enabling technique for the Naïve Bayes and semi-Naïve Bayes-based classification

3. R.Thaiphan and T.Phetkaew , Comparative Analysis of Discretization Algorithms on Decision Tree, in Proceedings - 17th IEEE / ACIS International Conference on Computer and Information Science, ICIS 2018 , 2018. 10.1109/ICIS.2018.8466449

4. J.Dougherty , R.Kohavi and M.Sahami , Supervised and Unsupervised Discretization of Continuous Features, in Machine Learning Proceedings 1995 , 1995. 10.1016/b978-1-55860-377-6.50032-3

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