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For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters.
Pathway based similarity measuring method, PEPC, consistently shows higher classification accuracies than CGSEP method for classifications with three different search databases.
Support Vector Machines [ 31] was used for classification of samples between two categories, and Diagonal Linear Discriminant Analysis, which avoids complex models with excessive parameters in order to avoid over fitting data without loss of performance [ 32] was used for classifications with more than two categories.
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Fig. 4 Accuracy result for classification with a NB classifier and a SVM classifer.
For classification with coarse spatial resolution data, limitations of the classification method produce a maximum achievable accuracy defined as the average percent fraction of dominant land cover of all pixels in the mapped area.
Fig. 7 Receiver operating curve for classification with CNN and classification based on areas.
With nine features, feed-forward neural network is used for classification with accuracy of 97%.
For classification with multiple classes, the majority class prediction or a inconclusive value could be used.
The preliminary analysis suggests that the features can be used for classification with Gaussian Mixture Models (GMM).
In the experiments with FA for classification with oracle segmentation, we assess different configurations for the number of x factors and the scoring methods described previously.
In the end, 60%% of the training data was used for classification, with the balance going for validation or accuracy assessment (Ramachandra et al. 2012c).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com