test

TrainerClass.py

@@ -213,15 +213,15 @@ class eNoseTrainer:
             output_dim = Y_trainc1D.shape[1]
 
             model = build_model_conv1D(config, input_shape, output_dim)
-            early_stopping = keras.callbacks.EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True)
+#            early_stopping = keras.callbacks.EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True)
 
             model.fit(
                 X_trainc1D, Y_trainc1D,
                 validation_data=(X_testc1D, Y_testc1D),
                 epochs=config['epochs'],
                 batch_size=config['batch_size'],
-                verbose=0,
-                callbacks=[early_stopping]
+                verbose=0
+#                callbacks=[early_stopping]
             )
 
             Y_pred = model.predict(X_testc1D)