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I'm trying to use stacking when predicting for the infamous Iris dataset. Also, I'd like to build to stacked classifier by myself which means I don't want to use mlxtend because it's too "easy" and out of the box. I'm using python 3 and working on windows 10.

I'm not having any issue choosing algorithms or during cross-validation but when I try to stack the base learners ( gaussian and multinomial naive bayes, logistic regression) which gave me a string answer : the species of iris ; with the meta-learner (gradient boosting classifier), I can't seem to have a string as an answer, only a probability and it my accuracy score is much lower than any of the individual base learner.

Could anyone direct me at some code and/or explanations as to what I should be doing instead?

Thanks a lot!

Nathan Furnal
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  • Can you share your attempt and your output respectively? – Aditya May 12 '18 at 18:08
  • Sadly, I deleted it out of spite but I didn't get anywhere (I know, not really smart) but I followed mostly [this](https://www.dataquest.io/blog/introduction-to-ensembles/) and I tried to copy from [this Kaggle notebook](https://www.kaggle.com/arthurtok/introduction-to-ensembling-stacking-in-python/code) but with no improvement. Thanks for your answer – Nathan Furnal May 12 '18 at 18:27

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