# 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?

• The reported error value depends on the cost function used. You have to choose an evaluation criterion and find the accuracy. I have to refer to something. In some occasions, even $60$% accuracy is highly acceptable, for instance, handwritten OCR, while for images which are taken from computer made fonts, even $99$% may not be appropriate. – Media Sep 30 '18 at 16:00