Hi,
For a classification problem, I need a short list of possible classes and
their confidence of predictions (to find a treshold classifier is 99%
sure).
I used a multiclass SVM. dataset has 1000 classes, 7-8 instances for each
and 2000 attributes. *.predict()* results are 72% accurate. However,
results from *.predict_proba()* didn't work well in this case. most
probable result is 30% accurate. .predict_proba() works different than
.predict()
http://stackoverflow.com/questions/15111408/how-does-sklearn-svm-svcs-function-predict-proba-work-internally
So, is there a way to calculate better predictions for ranking with
probabilities?
Thank you
--
Bilal Dadanlar
cimri.com | Software Engineer
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