

Project 'VGG16_1FC.Exp02.BonB.100p.unmasked.fold_2':
[1] "Model type 'VGG16_1FC' sucessfully initialized:"
$model
Model
Model: "sequential"
____________________________________________________________________________________________________________________________________________________________________
Layer (type)                                                             Output Shape                                                      Param #                  
====================================================================================================================================================================
vgg16 (Model)                                                            (None, 7, 7, 512)                                                 14714688                 
____________________________________________________________________________________________________________________________________________________________________
flatten (Flatten)                                                        (None, 25088)                                                     0                        
____________________________________________________________________________________________________________________________________________________________________
fc1 (Dense)                                                              (None, 256)                                                       6422784                  
____________________________________________________________________________________________________________________________________________________________________
Predictions (Dense)                                                      (None, 10)                                                        2570                     
====================================================================================================================================================================
Total params: 21,140,042
Trainable params: 6,425,354
Non-trainable params: 14,714,688
____________________________________________________________________________________________________________________________________________________________________



$classes
                                     name id
1                Asteromphalus.labId_6835  0
2                  Chaetoceros.labId_6813  1
3  Fragilariopsis kerguelensis.labId_8356  2
4      Fragilariopsis rhombica.labId_8362  3
5                    Nitzschia.labId_6758  4
6              Pseudonitzschia.labId_8364  5
7                 Rhizosolenia.labId_6776  6
8            Silicoflagellate.labId_10255  7
9      Thalassiosira gracilis.labId_10366  8
10  Thalassiosira lentiginosa.labId_10369  9

$inputShape
[1] 224 224

$optimizer
<tensorflow.python.keras.optimizers.Adam>

$callbacksList
list()

Data:
Classes: 10

Training: 1163 samples:
   ClassId                              ClassName Count Count.ANT31 Count.PS103
10       0               Asteromphalus.labId_6835    96           0          96
5        1                 Chaetoceros.labId_6813   211           0         211
8        2 Fragilariopsis kerguelensis.labId_8356   145           0         145
1        3     Fragilariopsis rhombica.labId_8362   128           0         128
9        4                   Nitzschia.labId_6758    25           0          25
2        5             Pseudonitzschia.labId_8364   208           0         208
4        6                Rhizosolenia.labId_6776    44           0          44
6        7           Silicoflagellate.labId_10255    99           0          99
3        8     Thalassiosira gracilis.labId_10366    74           0          74
7        9  Thalassiosira lentiginosa.labId_10369   133           0         133
11      NA                                    Sum  1163           0        1163

Validation: 296 samples:
   ClassId                              ClassName Count Count.ANT31 Count.PS103
8        0               Asteromphalus.labId_6835    24           0          24
2        1                 Chaetoceros.labId_6813    53           0          53
6        2 Fragilariopsis kerguelensis.labId_8356    37           0          37
5        3     Fragilariopsis rhombica.labId_8362    33           0          33
10       4                   Nitzschia.labId_6758     7           0           7
7        5             Pseudonitzschia.labId_8364    52           0          52
9        6                Rhizosolenia.labId_6776    12           0          12
4        7           Silicoflagellate.labId_10255    25           0          25
1        8     Thalassiosira gracilis.labId_10366    19           0          19
3        9  Thalassiosira lentiginosa.labId_10369    34           0          34
11      NA                                    Sum   296           0         296

Test: 484 samples:
   ClassId                              ClassName Count Count.ANT31 Count.PS103
9        0               Asteromphalus.labId_6835    40           0          40
1        1                 Chaetoceros.labId_6813    88           0          88
2        2 Fragilariopsis kerguelensis.labId_8356    60           0          60
6        3     Fragilariopsis rhombica.labId_8362    54           0          54
10       4                   Nitzschia.labId_6758    10           0          10
4        5             Pseudonitzschia.labId_8364    87           0          87
8        6                Rhizosolenia.labId_6776    18           0          18
7        7           Silicoflagellate.labId_10255    41           0          41
3        8     Thalassiosira gracilis.labId_10366    31           0          31
5        9  Thalassiosira lentiginosa.labId_10369    55           0          55
11      NA                                    Sum   484           0         484

Compiling Model:

Starting Training:
Epochs: 50
Batch size: 32


Evaluating trained model for project 'VGG16_1FC.Exp02.BonB.100p.unmasked.fold_2':


Model evaluation:
$confusionMatrix
Confusion Matrix and Statistics

          Reference
Prediction  0  1  2  3  4  5  6  7  8  9
         0 40  0  0  0  0  0  0  0  0  0
         1  0 87  0  0  0  1  0  0  0  0
         2  0  0 60  0  1  0  0  0  0  0
         3  0  0  0 54  0  0  0  0  0  0
         4  0  0  0  0  8  0  0  0  0  0
         5  0  1  0  0  1 86  0  0  0  0
         6  0  0  0  0  0  0 18  0  0  0
         7  0  0  0  0  0  0  0 41  0  0
         8  0  0  0  0  0  0  0  0 31  0
         9  0  0  0  0  0  0  0  0  0 55

Overall Statistics
                                         
               Accuracy : 0.9917         
                 95% CI : (0.979, 0.9977)
    No Information Rate : 0.1818         
    P-Value [Acc > NIR] : < 2.2e-16      
                                         
                  Kappa : 0.9905         
                                         
 Mcnemar's Test P-Value : NA             

Statistics by Class:

                     Class: 0 Class: 1 Class: 2 Class: 3 Class: 4 Class: 5 Class: 6 Class: 7 Class: 8 Class: 9
Precision             1.00000   0.9886   0.9836   1.0000  1.00000   0.9773  1.00000  1.00000  1.00000   1.0000
Recall                1.00000   0.9886   1.0000   1.0000  0.80000   0.9885  1.00000  1.00000  1.00000   1.0000
F1                    1.00000   0.9886   0.9917   1.0000  0.88889   0.9829  1.00000  1.00000  1.00000   1.0000
Prevalence            0.08264   0.1818   0.1240   0.1116  0.02066   0.1798  0.03719  0.08471  0.06405   0.1136
Detection Rate        0.08264   0.1798   0.1240   0.1116  0.01653   0.1777  0.03719  0.08471  0.06405   0.1136
Detection Prevalence  0.08264   0.1818   0.1260   0.1116  0.01653   0.1818  0.03719  0.08471  0.06405   0.1136
Balanced Accuracy     1.00000   0.9931   0.9988   1.0000  0.90000   0.9917  1.00000  1.00000  1.00000   1.0000

$statistics
   class                              className TP FP FN precision    recall        F1
1      0               Asteromphalus.labId_6835 40  0  0 1.0000000 1.0000000 1.0000000
2      1                 Chaetoceros.labId_6813 87  1  1 0.9886364 0.9886364 0.9886364
3      2 Fragilariopsis kerguelensis.labId_8356 60  1  0 0.9836066 1.0000000 0.9917355
4      3     Fragilariopsis rhombica.labId_8362 54  0  0 1.0000000 1.0000000 1.0000000
5      4                   Nitzschia.labId_6758  8  0  2 1.0000000 0.8000000 0.8888889
6      5             Pseudonitzschia.labId_8364 86  2  1 0.9772727 0.9885057 0.9828571
7      6                Rhizosolenia.labId_6776 18  0  0 1.0000000 1.0000000 1.0000000
8      7           Silicoflagellate.labId_10255 41  0  0 1.0000000 1.0000000 1.0000000
9      8     Thalassiosira gracilis.labId_10366 31  0  0 1.0000000 1.0000000 1.0000000
10     9  Thalassiosira lentiginosa.labId_10369 55  0  0 1.0000000 1.0000000 1.0000000

$macro
$macro$precision
[1] 0.9949516

$macro$recall
[1] 0.9777142

$macro$F1
[1] 0.9852118

$macro$F1.Sokolova_Lapalme
[1] 0.9862576


$micro
$micro$precision
[1] 0.9917355

$micro$recall
[1] 0.9917355

$micro$F1
[1] 0.9917355


