The new function backtest_ml() implemented in the example: "Machine Learning with a Voting Classifier" is a great way of getting a fast feedback from a given model.
Is it possible to use it with multiple datasets (for example, using "futures" and "commodity" data, as done in the template: "Futures - IMF Commodity") ?
@sun-73 thanks, sure, please let us a little bit of time to prepare an example with these specifications!
@support Many thanks! An example would be very much appreciated!
I tried to replicate the "Machine Learning with a Voting Classifier" example on strategy notebook, but I got the error message: "AttributeError: module 'qnt.backtester' has no attribute 'backtest_ml'".
Just update the library, it will be enough.
You can see the latest version of library here: https://anaconda.org/quantiacs-source/qnt/files
This command will update the package in the current environment.
conda install 'quantiacs-source::qnt>=0.0.255'
If you use pip, just reinstall the package from github:
pip install --force-reinstall git+git://github.com/quantiacs/toolbox.git
@sun-73 Hello, finally it is here:
Soon in the templates once we add some more text
@support Great! This route opens new possibilities in terms of model design. Thanks a lot!