Why not higher accuracy in Otto data? On this site of Otto Group Product Classification Challenge, it is shown that best accuracy was possible with RandomForest method, but it was relatively low at 0.83. Accuracy with ANN and with Naive Bayes was even lower (0.72 and 0.65, respectively). 

What is the cause of low accuracy achievable in some data? Are there any other methods with which accuracy can be increased here? 

Edit: On this site: https://www.kaggle.com/c/otto-group-product-classification-challenge/leaderboard best model seems to have a score of 0.38. What will be corresponding accuracy for that?
I can mention two main reasons.


Complexity of dataset
high Bayes error


The former means your dataset is highly non-linear and the latter simly means you may have same input with contradictory outputs in your dataset.