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Table 5 Predictions on five datasets in terms of units_r

From: Occurrence prediction of pests and diseases in cotton on the basis of weather factors by long short term memory network

Units_rMetricsP1P2P3P4P5
4ACC0.92410.89730.91110.90170.8742
 AUC0.97120.95320.96870.95780.9465
 F1-score0.88570.82580.83160.87370.7804
5ACC0.93290.91690.91760.91360.8903
 AUC0.97640.96740.96630.97040.9715
 F1-score0.89490.85550.85800.89550.7903
6ACC0.92810.90630.90980.89490.8968
 AUC0.97370.96430.95290.96280.9649
 F1-score0.88960.84500.84200.86800.8234
7ACC0.92760.90130.92550.90000.9032
 AUC0.97100.95570.97170.95510.9636
 F1-score0.88700.82050.85840.87630.8104
  1. The entry in boldface represents the best performance on one dataset with respect of Units_r
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