Homogeneity Test for Confusion Matrices: A Method and an Example

The confusion matrix is the standard way to report on the thematic accuracy of geographic information data. Two widely adopted indices for thematic accuracy controls upon error matrix are the overall accuracy and the Kappa coefficient. Provided that a multinomial sampling, this work proposes a new m...

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Bibliographic Details
Published inIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium pp. 1203 - 1205
Main Authors Garcia-Balboa, Jose L., Alba-Fernandez, Maria V., Ariza-Lopez, Francisco J., Rodriguez-Avi, Joso
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2018
Subjects
Computational modeling
confusion matrix
Hellinger distance
Indexes
ISO Standards
Proposals
Remote sensing
Testing
Thematic accuracy
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Summary:The confusion matrix is the standard way to report on the thematic accuracy of geographic information data. Two widely adopted indices for thematic accuracy controls upon error matrix are the overall accuracy and the Kappa coefficient. Provided that a multinomial sampling, this work proposes a new method for testing the homogeneity of two independent thematic classifications which is based on whole error matrices. Specifically, a test function is proposed that uses as a test statistic the discrete Hellinger distance, which null distribution is approximated by bootstrapping. The performance of this approximation is evaluated by simulation, which confirms that it behaves properly, especially for small and moderate sample sizes. Finally an example of application is included.
ISSN:2153-7003
DOI:10.1109/IGARSS.2018.8517924