

Project 'VGG16_1FC.Exp16.BonA.10p.masked.run_4':
[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: 150 samples:
   ClassId                              ClassName Count Count.ANT31 Count.PS103
6        0               Asteromphalus.labId_6835    12           0          12
1        1                 Chaetoceros.labId_6813    28           0          28
3        2 Fragilariopsis kerguelensis.labId_8356    19           0          19
5        3     Fragilariopsis rhombica.labId_8362    17           0          17
7        4                   Nitzschia.labId_6758     3           0           3
4        5             Pseudonitzschia.labId_8364    28           0          28
2        6                Rhizosolenia.labId_6776     5           0           5
9        7           Silicoflagellate.labId_10255    12           0          12
10       8     Thalassiosira gracilis.labId_10366     9           0           9
8        9  Thalassiosira lentiginosa.labId_10369    17           0          17
11      NA                                    Sum   150           0         150

Validation: 43 samples:
   ClassId                              ClassName Count Count.ANT31 Count.PS103
5        0               Asteromphalus.labId_6835     4           0           4
3        1                 Chaetoceros.labId_6813     7           0           7
4        2 Fragilariopsis kerguelensis.labId_8356     5           0           5
2        3     Fragilariopsis rhombica.labId_8362     5           0           5
10       4                   Nitzschia.labId_6758     1           0           1
1        5             Pseudonitzschia.labId_8364     7           0           7
9        6                Rhizosolenia.labId_6776     2           0           2
7        7           Silicoflagellate.labId_10255     4           0           4
8        8     Thalassiosira gracilis.labId_10366     3           0           3
6        9  Thalassiosira lentiginosa.labId_10369     5           0           5
11      NA                                    Sum    43           0          43

Test: 138 samples:
   ClassId                              ClassName Count Count.ANT31 Count.PS103
8        0               Asteromphalus.labId_6835     6           6           0
9        1                 Chaetoceros.labId_6813     8           8           0
5        2 Fragilariopsis kerguelensis.labId_8356    42          42           0
10       3     Fragilariopsis rhombica.labId_8362     6           6           0
3        4                   Nitzschia.labId_6758     8           8           0
7        5             Pseudonitzschia.labId_8364    17          17           0
1        6                Rhizosolenia.labId_6776    15          15           0
2        7           Silicoflagellate.labId_10255    18          18           0
4        8     Thalassiosira gracilis.labId_10366     9           9           0
6        9  Thalassiosira lentiginosa.labId_10369     9           9           0
11      NA                                    Sum   138         138           0

Compiling Model:

Starting Training:
Epochs: 50
Batch size: 8


Evaluating trained model for project 'VGG16_1FC.Exp16.BonA.10p.masked.run_4':


Model evaluation:
$confusionMatrix
Confusion Matrix and Statistics

          Reference
Prediction  0  1  2  3  4  5  6  7  8  9
         0  6  0  0  0  0  0  0  0  0  0
         1  0  7  0  1  0  0  1  1  0  0
         2  0  0 39  0  0  0  0  0  0  0
         3  0  0  2  5  0  0  0  0  0  0
         4  0  0  1  0  7  0  0  0  0  0
         5  0  0  0  0  1 17  0  0  0  0
         6  0  1  0  0  0  0 14  0  0  0
         7  0  0  0  0  0  0  0 17  0  0
         8  0  0  0  0  0  0  0  0  9  0
         9  0  0  0  0  0  0  0  0  0  9

Overall Statistics
                                         
               Accuracy : 0.942          
                 95% CI : (0.889, 0.9746)
    No Information Rate : 0.3043         
    P-Value [Acc > NIR] : < 2.2e-16      
                                         
                  Kappa : 0.9318         
                                         
 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  0.70000   1.0000  0.71429  0.87500   0.9444   0.9333   1.0000  1.00000  1.00000
Recall                1.00000  0.87500   0.9286  0.83333  0.87500   1.0000   0.9333   0.9444  1.00000  1.00000
F1                    1.00000  0.77778   0.9630  0.76923  0.87500   0.9714   0.9333   0.9714  1.00000  1.00000
Prevalence            0.04348  0.05797   0.3043  0.04348  0.05797   0.1232   0.1087   0.1304  0.06522  0.06522
Detection Rate        0.04348  0.05072   0.2826  0.03623  0.05072   0.1232   0.1014   0.1232  0.06522  0.06522
Detection Prevalence  0.04348  0.07246   0.2826  0.05072  0.05797   0.1304   0.1087   0.1232  0.06522  0.06522
Balanced Accuracy     1.00000  0.92596   0.9643  0.90909  0.93365   0.9959   0.9626   0.9722  1.00000  1.00000

$statistics
   class                              className TP FP FN precision    recall        F1
1      0               Asteromphalus.labId_6835  6  0  0 1.0000000 1.0000000 1.0000000
2      1                 Chaetoceros.labId_6813  7  3  1 0.7000000 0.8750000 0.7777778
3      2 Fragilariopsis kerguelensis.labId_8356 39  0  3 1.0000000 0.9285714 0.9629630
4      3     Fragilariopsis rhombica.labId_8362  5  2  1 0.7142857 0.8333333 0.7692308
5      4                   Nitzschia.labId_6758  7  1  1 0.8750000 0.8750000 0.8750000
6      5             Pseudonitzschia.labId_8364 17  1  0 0.9444444 1.0000000 0.9714286
7      6                Rhizosolenia.labId_6776 14  1  1 0.9333333 0.9333333 0.9333333
8      7           Silicoflagellate.labId_10255 17  0  1 1.0000000 0.9444444 0.9714286
9      8     Thalassiosira gracilis.labId_10366  9  0  0 1.0000000 1.0000000 1.0000000
10     9  Thalassiosira lentiginosa.labId_10369  9  0  0 1.0000000 1.0000000 1.0000000

$macro
$macro$precision
[1] 0.9167063

$macro$recall
[1] 0.9389683

$macro$F1
[1] 0.9261162

$macro$F1.Sokolova_Lapalme
[1] 0.9277038


$micro
$micro$precision
[1] 0.942029

$micro$recall
[1] 0.942029

$micro$F1
[1] 0.942029


