Looks like an idea for a semi-supervised ensemble method for machine learning: Prepare two equally sized ensembles of classifiers, let's call them A and B. 1.

Looks like an idea for a semi-supervised ensemble method for machine learning: Prepare two equally sized ensembles of classifiers, let's call them A and B. 1. Train each classifier in ensemble A on labelled data to predict does a picture contains a cat. 2. Take some other unlabelled dataset and collect answers from classifiers from A for each picture from this dataset. 3. Train each classifier in ensemble B to predict average answer of classifiers from A for each picture from the unlabelled dataset. Then for a picture from the test dataset it would be possible to get answers from ensemble A and from ensemble B and calculate what would be the surprisingly popular answer.