Here are some results for ANN and KNN on abalone data set using Weka:
Result for ANN Correctly Classified Instances 3183 76.203 % Incorrectly Classified Instances 994 23.797 % Mean absolute error 0.214 Root mean squared error 0.3349 Relative absolute error 58.6486 % Result for KNN Correctly Classified Instances 3211 76.8734 % Incorrectly Classified Instances 966 23.1266 % Mean absolute error 0.2142 Root mean squared error 0.3361 Relative absolute error 58.7113 %
KNN has high accuracy but ANN has low errors. So which of the two algorithms should I say is better?
Which is the more preferable criterion, accuracy or error?
What I understood was that error should decrease with high accuracy, but the results here are opposite. Why is this so?