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ResulttsProves.txt
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ResulttsProves.txt
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Prova 1:
Arxiu: ModelconCMatrix
model utilitzat:VGG16 botleneck +
model = Sequential()
#model.add(Flatten())
model.add(Flatten(input_shape=train_data.shape[1:]))
model.add(Dense(256, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(6, activation='softmax'))
Resultats:
print(confusion_matrix(test_generator.classes, ypred))
[[ 15 14 19 8 49 85]
[ 20 45 24 0 89 43]
[ 15 3 7 18 11 11]
[ 27 9 28 5 17 16]
[ 17 32 15 6 66 35]
[114 14 45 14 29 17]]
history.history['accuracy']
Out[31]:
[0.29190016,
0.32934284,
0.34335202,
0.36347428,
0.3782476,
0.38588893,
0.3909832,
0.41161487,
0.42969945,
0.43326542,
0.43963322,
0.44727457,
0.46408558,
0.48420784,
0.46968925,
0.47834948,
0.50050944,
0.50152826,
0.50916964,
0.52496177,
0.5295466,
0.53667855,
0.5458482,
0.55578196,
0.5649516,
0.57488537,
0.56546104,
0.5649516,
0.5746307,
0.58074373,
0.5799796,
0.5939888,
0.5965359,
0.5927152,
0.5947529,
0.61665815,
0.61665815,
0.621243,
0.6125828,
0.62175244,
0.6268467,
0.62812024,
0.63779926,
0.64136523,
0.6372899,
0.6487519,
0.6319409,
0.6357616,
0.636271,
0.6444218]