Adaboost for 3D Input data I want to do a text classification problem for which I want to train use Adaboost Classifier from sklearn using a Keras estimator. I do know how to use the Keras wrappers for using sklearn functions. So that is not the problem. I have a 3D input data (number_sentences, number_words, features) and when I checked the source code of Adaboost, it shows that X can be only 1D or 2D. 


Why is that so? 
Is there any other way for me to use Adaboost for 3D    input data?
Adaboost doesn't care about the order of the features, so no matter how many dimensions your samples have, you can just flatten them. Flattening them gives you a 2D X with shape (n_samples, n_features) which you can feed to the Adaboost classifier.