Validate classifiers against the labeled ambiguous data

[martinthenext]

Implement a procedure to measure agreement of a classifier with the labeled ambiguous data. For that purpose:

1. Annotation class should be modified to store ambiguous data as well
2. Function should be implemented in data.py to deserialize labeled ambiguous data (from MTurk or expert) to a list of Annotation objects.
3. Module should be implemented to test classifiers against this data - analogous to cv.py

[martinthenext]

Input data format for labeled data can be viewed here:

https://kitt.cl.uzh.ch/kitt/mantracrowd/disambig/vote_results.csv?AgreementThr=0.6

where AgreementThr designates agreement threshold