data-mining

Summary

mypy shows some issues in LightGBM's Python package.

mypy \
    --exclude='python-package/compile/|python-package/build' \
    --ignore-missing-imports \
    python-package/

python-package/lightgbm/compat.py:12: error: Name 'Series' already defined (possibly by an import)
python-package

In gensim/models/fasttext.py:

    model = FastText(
        vector_size=m.dim,
        vector_size=m.dim,
        window=m.ws,
        window=m.ws,
        epochs=m.epoch,
        epochs=m.epoch,
        negative=m.neg,
        negative=m.neg,
        # FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
        # or model=3 supervi

It would be great to have FBeta, F2, or F0.5 metrics to be implemented without the need for a custom metric class defined by user.

catboost version: 0.26

The official instructions say to use joblib for pickling PyOD models.

This fails for AutoEncoders, or any other TensorFlow-backed model as far as I can tell. The error is:

>>> dump(model, 'model.joblib')
...
TypeError: can't pickle _thread.RLock objects

Note that it's not sufficient to save the underlying Keras S

It's been awhile since I updated e2e tests and there are some of them that are filing (most of them are related to examples).

Also, we need to add e2e tests that cover headers and cookies for both drivers.

Is your feature request related to a problem? Please describe.
EnsembleForecaster does not currently accept weights. With #1136 and #1139 being worked on it would be nice to optionally allow users to pass weights to EnsembleForecaster.

This would give users an out-of-the-box way to use ainverse error based weighting strategy in forecasting ensembles. Users could also supply other types

What's wrong?