Performance Metrics: How and When

@article{Israel2006PerformanceMH,
  title={Performance Metrics: How and When},
  author={Steven A. Israel},
  journal={Geocarto International},
  year={2006},
  volume={21},
  pages={23 - 32}
}
  • S. Israel
  • Published 1 June 2006
  • Mathematics
  • Geocarto International
Abstract This paper compares different classification performance metrics commonly used for environmental monitoring with remotely sensed satellite data and their associated error bounds. Discriminant functions were generated for three classifiers using common training data. Identical independent test data were classified by each discriminant function. The classified test values were evaluated by each performance metric. Each performance measure, its error bound, and its significance were… 
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References

SHOWING 1-10 OF 33 REFERENCES
Tau coefficients for accuracy assessment of classification of remote sensing data
The Kappa coefficient is generally used to assess the accuracy of image classifications. We introduce the Tau coefficient, which measures the improvement of a classification over a random assignment
A coefficient of agreement as a measure of thematic classification accuracy.
The classification error matrix typically contains tabulated results of accuracy evaluation for a thematic classification, such as a land-use and land-cover map. Diagonal elements of the matrix
A multinomial selection procedure for evaluating pattern recognition algorithms
Status of land cover classification accuracy assessment
Discriminant Analysis and Statistical Pattern Recognition
Provides a systematic account of the subject area, concentrating on the most recent advances in the field. While the focus is on practical considerations, both theoretical and practical issues are
On the classification of multispectral satellite images using the multilayer perceptron
Assessing the accuracy of remotely sensed data : principles and practices
TLDR
This chapter discusses Accuracy Assessment, which examines the impact of sample design on cost, statistical Validity, and measuring Variability in the context of data collection and analysis.
A land-use classification system for use with remote sensor data
New demands on our land resources require more stringent controls and management practices. The administration of these controls requires better and more frequent information concerning land use.
The effect of training set size and composition on artificial neural network classification
TLDR
The results showed that higher classification accuracies were generally derived from the artificial neural network, especially when small training sets only were available, and it was apparent that the opportunity of the artificial Neural Network to learn class appearance was influenced by the composition of the training set.
On the compensation for chance agreement in image classification accuracy assessment, Photogram
TLDR
Two kappa-like approaches which compensate more appropriately for the degree of chance agreement are discussed, and they may be more suitable for the assessment of image classification accuracy than the kappa coefficient.
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