Supplementary_Table_T1. Classifier Performance in the Validation Stage of the Iba-1 Dataset,,,,,,
classifier,precision,recall,F1,accuracy,MAE,MPE
classifier4,0.94856661,0.815217391,0.87685113,0.780707842,19.4,0.014057971
classifier2,0.944915254,0.807971014,0.87109375,0.771626298,20,0.014492754
classifier10,0.971243043,0.758695652,0.851912124,0.742026931,30.2,0.021884058
classifier5,0.968605725,0.760144928,0.85180674,0.741867044,29.7,0.021521739
classifier9,0.971857411,0.750724638,0.847097302,0.734751773,31.4,0.022753623
classifier8,0.970037453,0.750724638,0.846405229,0.733711048,31.2,0.022608696
classifier21,0.976099426,0.739855072,0.841714757,0.726690391,33.4,0.024202899
classifier11,0.972407231,0.74057971,0.840806253,0.725337119,32.9,0.02384058
classifier7,0.972354623,0.739130435,0.839851791,0.723917672,33.1,0.023985507
classifier6,0.973051011,0.732608696,0.835882596,0.718039773,34.1,0.024710145
classifier12,0.97024952,0.732608696,0.834847234,0.716513111,33.8,0.024492754
classifier23,0.979431929,0.724637681,0.832986256,0.713775874,35.9,0.026014493
classifier22,0.978431373,0.723188406,0.831666667,0.711840228,36,0.026086957
classifier20,0.975609756,0.724637681,0.831600832,0.711743772,35.5,0.025724638
classifier19,0.97745098,0.722463768,0.830833333,0.7106201,36,0.026086957
classifier14,0.978239367,0.716666667,0.827268925,0.705420827,36.9,0.02673913
classifier24,0.978174603,0.714492754,0.825795645,0.703281027,37.2,0.026956522
classifier18,0.981,0.710869565,0.824369748,0.701215154,38,0.027536232
classifier13,0.972222222,0.710144928,0.820770519,0.696022727,37.2,0.026956522
classifier25,0.977732794,0.7,0.815878378,0.689015692,39.2,0.028405797
classifier15,0.977412731,0.689855072,0.808836024,0.679029957,40.6,0.02942029
classifier16,0.975409836,0.689855072,0.808149406,0.678062678,40.4,0.029275362
classifier17,0.977249224,0.684782609,0.80528334,0.67403709,41.3,0.029927536
classifier1,0.973190349,0.526086957,0.682972719,0.518571429,63.4,0.045942029
classifier3,0.968571429,0.245652174,0.391907514,0.243709561,103,0.074637681
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"Classifiers are trained iteratively in TWS using small additions in training data. Reported statistics are calculated from the total of all cells in each image in the dataset except for MAE and MPE(n = 10 images). Statistics include the following categories. Precision which is the number of true positive automaticly counted cells divided by the total number of automaticly counted cells. Recall which is the number of true positive automaticly counted cells divided by the total number of hand placed counts. F1 which is the harmonic average of precision and recall. Accuracy which is the number of true positive automaticly counted cells divided by the total of the number of automaticly counted cells plus false negatives. MAE is mean absolute error between predicted counts and hand counts. Finally, MPE is the mean percent error between predicted counts and hand counts.",,,,,,