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Yes, I am having the same problem. I was able to modify the Backtest class to get new data, but tflearn will not accept the new history for training. Any help would be appreciated.
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In backtesting there are two options to test model online or offline.
Online : Takes data from poloniex and updates database
Offline : Using pre-collected datas in Data.db
Backtesting module using rollingtrainer's datamatrix and it takes all datas from database at the begginning of the backtest.
But I couldn't find a way to get new data and process it .
It is using day based date to take data in given day based interval.
Is there any module to update database dynamically for livetrading without resetting learning of the model ?
from pgportfolio.
Is there any module to update database dynamically for livetrading without resetting learning of the model ?
A simple(while not elegant) method is to append new data to the global_data (Panel in the memory) and modify all the related indexes.
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I am doing this for real time data ;
- last input X: global_data[: , :, -window_size:]
- apply action according to X
- Wait n-minutes
- get input again
- y : newX[:, :, -1] / newX[:, :, -2]
But couldn't solve the how to use thid x, y data to update RL agent.
I think RL training must be always active for the understand every new situation , but it seems it don't train model in backtesting part adding None object to experience tracker module.
Also thank you for first fast reply :)
from pgportfolio.
Thank you for the hints @ZhengyaoJiang and @redzhepdx, will give it another go now!
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