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from keras.models import load_model
import numpy
dataset = numpy.loadtxt("wine-data.csv", delimiter=";")
input = dataset[:, 0:11]
output = dataset[:, 11]
# since the data comes in a scale of 0 to 10, this is needed to we get a simple true or false
output = [(round(each / 10)) for each in output]
model = load_model('wine-model.h5')
scores = model.evaluate(input, output)
print("\n%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))
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