Implement predict_proba as per #138

[Mec-iS]

See #138

Last test fit_predict_probabilities is failing, I don't know if because of the implementation or I am missing something in replicating the test in sklearn:

from sklearn.ensemble import RandomForestClassifier

clf = RandomForestClassifier(criterion="gini")
clf.fit(x, y)
print(clf.predict_proba(x))

[[0.99 0.01]
 [0.82 0.18]
 [0.97 0.03]
 [0.8  0.2 ]
 [0.99 0.01]
 [0.9  0.1 ]
 [0.99 0.01]
 [0.91 0.09]
 [0.23 0.77]
 [0.4  0.6 ]
 [0.   1.  ]
 [0.   1.  ]
 [0.   1.  ]
 [0.   1.  ]
 [0.   1.  ]
 [0.   1.  ]
 [0.01 0.99]
 [0.02 0.98]
 [0.   1.  ]
 [0.01 0.99]]

[dlrobson]

Hey guys! My team and I have just started using this library for our project. This functionality would be awesome for what we're doing. Is there any update on the progress of this?

[morenol]

Hey guys! My team and I have just started using this library for our project. This functionality would be awesome for what we're doing. Is there any update on the progress of this?

Hey, I think that there have not been more updates, none of the contributors have had time to finish it

[Mec-iS]

Hey guys! My team and I have just started using this library for our project. This functionality would be awesome for what we're doing. Is there any update on the progress of this?

It would be nice to have somebody with understanding of this feature, please help if you know how to implement this. It seems there are some differences between the results returned by smartcore and the ones returned by sklearn.