NDLI: Proper comparison among methods using a confusion matrix

Content Provider	IEEE Xplore Digital Library
Author	Salmon, B.P. Kleynhans, W. Schwegmann, C.P. Olivier, J.C.
Copyright Year	2015
Description	Author affiliation: Sch. of Eng. & ICT, Univ. of Tasmania, Hobart, TAS, Australia (Olivier, J.C.) \|\| Remote Sensing Res. Unit, Meraka Inst., Pretoria, South Africa (Salmon, B.P.) \|\| Dept. of Electr., Univ. of Pretoria, Tshwane, South Africa (Kleynhans, W.; Schwegmann, C.P.)
Abstract	An important aspect of research in the remote sensing field is to objectively compare different classifiers. This is the foundation of hundreds of research projects and in this paper we will address some raising concerns when evaluating solutions for classification of data sets with skewed class distributions. The quality of assessment is based on the problem specified by the user and the corresponding hypothesis defined. This hypothesis will determine how two or more classifiers are scored to determine which one is better for a particular application. In this paper we present two experiments that illustrate how, if unaware and misunderstood, statistical measurements can be misleading. One experiment is based on a Synthetic Aperture Radar image with a highly skewed class distribution and the second experiment is based on a Landsat image with a minor skewed distribution. From both experiments it can be seen that ill-defining the problem, can lead to false statements and the reporting of statistically invalid conclusions.
Starting Page	3057
Ending Page	3060
File Size	309312
Page Count	4
File Format	PDF
e-ISBN	9781479979295
DOI	10.1109/IGARSS.2015.7326461
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Satellites Earth Marine vehicles Measurement Accuracy Oceans Statistics Image classification Probability distribution Remote Sensing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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