YAO/YAO-optimizer
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Newnius
2020-05-02 11:17:49 +08:00
parent d53554d3b5
commit f84743b291
2 changed files with 5 additions and 4 deletions
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7
train.py
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@@ -90,7 +90,8 @@ def experiment(repeats, series, seed):
supervised = timeseries_to_supervised(diff_values, lag2)
supervised_values = supervised.values
# split data into train and test-sets
train, test = supervised_values[0:-12], supervised_values[-12:]
test_data_num = 4
train, test = supervised_values[0:-test_data_num], supervised_values[-test_data_num:]
# transform the scale of the data
print(test)
scaler, train_scaled, test_scaled = scale(train, test)
@@ -127,8 +128,8 @@ def experiment(repeats, series, seed):
# store forecast
predictions.append(yhat)
# report performance
rmse = sqrt(mean_squared_error(raw_values[-12:], predictions))
print(predictions, raw_values[-12:])
rmse = sqrt(mean_squared_error(raw_values[-test_data_num:], predictions))
print(predictions, raw_values[-test_data_num:])
print('%d) Test RMSE: %.3f' % (r + 1, rmse))
error_scores.append(rmse)
return error_scores