Understanding log_loss

I read somewhere on this forum that last years winner had only 18 misclassification’s. That made me suspicious way my submitted model is only in 126 place on a leader-board( my current result is 42 True predictions and 14 False ones). It seems that if I would had made my predictions more aggressive, something like: if pred> 0.5: pred==0.95 else: pred==0.05My log_loss would be 0.34, instead of 0.53. I’m curious is this common case to manually edit your probabilities or other classifiers like neural networks ( never tried it) just predicting with higher confidence ? I’ve used SVC(‘rbf”).

Link to Full Article: Understanding log_loss

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