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I am working on classifying texts and images of scientific articles. From the texts I use title and abstract. So far I have achieved good results using an SVM for the texts and not that good using a CNN for the images. I still did a multimodal classification, which did not show any classification improvement.

What I would like to do now is to use the svm and cnn predictions to classify, something like a vote ensemble. However the VotingClassifier from sklearn does not accept mixed inputs. You would have some idea of how I could implement or some guide line.

Thank you!

petezurich
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Bruna Brandão
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    This question might be a better fit for [Cross Validated](https://stats.stackexchange.com/) or [Data Science](https://datascience.stackexchange.com/) sites (but do check their help pages to see what kind of questions they accept). It's probably a bit too general for Stack Overflow itself, which is more concerned with solving specific programming problems. – snakecharmerb Feb 17 '19 at 14:37

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One simple thing you can do is take the outputs from both your models and just use them as inputs to third linear regression model. This effectively "mixes" your 2 learners into a small ensemble. Of course this is a very simple strategy but it might give you a slight boost over using each model separately.

Eugen Hotaj
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