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# Visualize training history
from keras.models import Sequential
from keras.layers import Dense
import matplotlib.pyplot as plt
import numpy
# fix random seed for reproducibility
seed = 7
numpy.random.seed(seed)

class History(object):
    def __init__(self):
        self.history= {'acc':[1,2,3,4,5,6], 'val_acc':[1,3,4,5,5,6]}
        pass
    
history = History()
# list all data in history
print(history.history.keys())
# summarize history for accuracy
plt.plot(history.history['acc'])
plt.plot(history.history['val_acc'])
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(['train', 'test'], loc='upper left')
plt.show()


    

    




dict_keys(['val_acc', 'acc'])






    

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