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I might be missing something, please correct me if so but I believe this model is predicting exactly 1 step behind at all times. Whenever I look at the time of the predictions it's always in the past, including day predictions.
For example, at 5:42:
2019-06-14 05:41:48] Fetching BTC_ETH: https://poloniex.com/public?command=returnChartData¤cyPair=BTC_ETH&start=1555555555&end=4294967296&period=300
[2019-06-14 05:41:51] Fetched BTC_ETH (5m)
C:\Users\username\Desktop\time-series-machine-learning-master\time-series-machine-learning-master\util\data_util.py:74: FutureWarning: Method .as_matrix will be removed in a future version. Use .values instead.
row = window.as_matrix().reshape((-1,))
[2019-06-14 05:42:04] Latest chart info:
close high low open quoteVolume volume weightedAverage
date
2019-06-14 05:35:00 0.03093 0.03093 0.030915 0.03093 34.577163 1.068963 0.030915
2019-06-14 05:40:00 0.03093 0.03093 0.030930 0.03093 0.028200 0.000872 0.030930
[2019-06-14 05:42:04] Prediction for "high":
Prediction Current-Truth
Time
2019-06-14 05:40:00 0.03093 0.03093
Using the same http link just before I run the command I can see that there's that exact result at 5:40.
It's not predicting ahead, it's already there. Am I missing something?
The text was updated successfully, but these errors were encountered:
I might be missing something, please correct me if so but I believe this model is predicting exactly 1 step behind at all times. Whenever I look at the time of the predictions it's always in the past, including day predictions.
For example, at 5:42:
Using the same http link just before I run the command I can see that there's that exact result at 5:40.
It's not predicting ahead, it's already there. Am I missing something?
The text was updated successfully, but these errors were encountered: