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The random forest model had the highest overall accuracy (84%) and Cohen's kappa coefficient (0.62).
The combination of enlargement and firmness had the highest overall accuracy (93.3%).
Each model performed with high accuracy and was incorporated into an ensemble model, which performed with the highest overall accuracy of all the models.
Of the 5 soil family classes we map, the highest overall accuracy (0.71) and kappa index (0.69) are achieved using the DTA and ANN method.
The hybrid endmember selection technique resulted in the highest overall accuracy and kappa values and proved to be least sensitive to the random sampling protocols, but also produced the largest spectral libraries.
High density LiDAR yielded the highest overall accuracy of building type detection and proved useful for identifying roof features, yet lower densities proved more useful for revealing overall roof morphology.
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Compared with the state-of-the-art prediction methods, the proposed method achieves the highest overall accuracies on all the three datasets.
The results show that the proposed classification produced the highest overall accuracies and kappa coefficients, and the smallest over-classification and under-classification geometric errors.
The species stratification with only three classes (Spmax) was most simple to predict and these predictions also yielded the highest overall accuracies of 73.6 and 76.2 % and kappa coefficients 0.40 and 0.48 using 3 and 4 predictors, respectively.
IslandPath-DIMOB and SIGI-HMM both have the highest overall accuracies for sequence composition-based prediction of GIs to date, but with lower sensitivity/recall than IslandPath-DINUC [18].
The classification results showed high overall accuracy (above 92.5%) and kappa coefficient (above 0.91).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com