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?