Artem Golubin

You are right. I think I've removed it accidentally. That was a model from keras.

Yes, because in the code, I didn't add it to the pipeline. I just demonstrated how to use functions.

Yes, it's possible. You can implement this logic inside your custom model or just add new datasets. ``` def xgboost_model(X_train, y_train, X_test, y_test=None, random_state=9999): params = { 'objective': 'reg:linear', 'learning_rate':...

You can use this article as a reference: http://mlwave.com/kaggle-ensembling-guide/ I'm not aware of good papers describing ensemble learning.

No, I don't have it.

Hi, we already have a tree algorithm. Because a lot of ensemble algorithms use it.

You can copy `mla` directory into `examples`. I don't know what kind of IDE you are using, but PyCharm can automatically detect `examples` directory.

1. There are tens of functions in the deep learning module. I prefer simplicity, so everyone can understand the concept behind this. 2. Flexibility. People can play around with custom...

I've checked exactly the same configuration, it's working for me. ``` Python 2.7.12 :: Anaconda 4.2.0 (x86_64) ProductName: Mac OS X ProductVersion: 10.12.1 BuildVersion: 16B2555 ```

Can you please make a PR with the fix?