Project is only code based (no ui or terminal commands) and focused on building regresion model for crypto u will choose from dataset (~/data/
dir).
For detailed data research and model research check files: ~/data_research.ipynb
and ~/model_research.ipynb
.
Go to ~/main.py
and on 8 row select your crypto from ~/data/
. Example:
dpp.process_whole_stock_data('bitcoin')
Returns training / prediction metricks and plots diagram for check data correctness. Example output:
foo@bar:stock-predictor$ pip3 install -r requirements.txt && python3 main.py
Train time: 0.0047833919525146484 seconds
Train MSE: 76490.93
Train R2: 99.96%
Train MAPE: 22.50%
Actual Predicted Date
0 0.1 -0.599570 -1.731659
1 0.1 -0.650913 -1.730875
2 0.1 -0.649552 -1.730092
3 0.1 -0.648234 -1.729308
4 0.1 -0.647001 -1.728524
... ... ... ...
4415 20831.3 21607.906886 1.728524
4416 21138.9 21170.545010 1.729308
4417 21517.2 21491.744238 1.730092
4418 21416.3 21032.574638 1.730875
4419 21309.0 21252.596035 1.731659