modAL 0.3.5

Changes

• ActiveLearner now supports np.nan and np.inf in the data by setting force_all_finite=False upon initialization. #58
• Bayesian optimization fixed for multidimensional functions.
• Calls to check_X_y no longer converts between datatypes. #49
• Expected error reduction implementation error fixed. #45
• modAL.utils.data_vstack now falls back to numpy.concatenate if possible.
• Multidimensional data for ranked batch sampling and expected error reduction fixed. #41

Fixes by @zhangyu94:

• modAL.selection.shuffled_argmax #32
• Cold start instance in modAL.batch.ranked_batch fixed. #30
• Best instance index in modAL.batch.select_instance fixed. #29