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The inclusion of texture information in the classification did not improve the classification quality.
Considering that the features may contain many relations in real life, we try to capture the relations among these features to improve the classification quality.
While the statistic without the unclassified pixels provides less than a complete picture of the classification quality, it is a valuable measure of the classifier's pattern matching capability and its sensitivity to uncertainty.
According to Figure S2, the classification quality of the discriminatory model remained high and stable in both datasets, even though Dataset L was much smaller than Dataset M. Combining these performance data obtained by both the inter-dataset (Table S3) and intra-dataset (Figure S2) training and testing, the feasibility and robustness of the proposed DS detection methods was confirmed again.
In order to assess the classification quality, we consider the sensitivity (SE) and specificity (SP) measures.
Generalization of the rules did not lead to any significant deterioration of the classification quality.
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The final classification quality was not affected by the year of cultivation, moisture content or grain variety.
That is, exclusion of the best performing features from the pool shows whether they are crucial for the good classification quality or there are other subsets that perform nearly as well.
To efficiently analyze the data, a new metric for assessment of data utility, the combined classification quality measure, was developed.
Then, the overall F-measure score can be calculated with precision and recall, which could measure the overall classification quality of multiclass problems.
The detailed classification qualities measured by the Area Under the ROC Curve (AUC) in a10-fold cross-validation can be found in Table 1.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com