def test(self):
test_loss, test_pred = self.trainer.test(self.test_dataset)
test_pearson = self.metrics.pearson(test_pred,
self.test_dataset.labels)
test_mse = self.metrics.mse(test_pred, self.test_dataset.labels)
(test_f1, test_prec, test_rec,
test_bestThreshold) = Helper.calculate_f1(test_pred,
self.test_dataset.labels,
True, True)
print('==> Test \tLoss: {}\tPearson: {}\tMSE: {}\tF1: {}'.format(
test_loss, test_pearson, test_mse, test_f1))
return test_f1, test_bestThreshold
def test_on_train(self):
print("test_on_train():")
exit()
highest_test_f1 = 0
test_loss, test_pred = self.trainer.test(self.train_dataset)
test_pearson = self.metrics.pearson(test_pred,
self.train_dataset.labels)
test_mse = self.metrics.mse(test_pred, self.train_dataset.labels)
(test_f1, test_prec, test_rec,
test_bestThreshold) = Helper.calculate_f1(test_pred,
self.train_dataset.labels,
True, True)
print('==> Test \tLoss: {}\tPearson: {}\tMSE: {}\tF1: {}'.format(
test_loss, test_pearson, test_mse, test_f1))
if test_f1 > highest_test_f1:
highest_test_f1 = test_f1
print("**** highest_test_f1:", highest_test_f1)
