Ringnorm data set 1: Description. This is a 20 dimensional, 2 class classification problem. Each class is drawn from a multivariate normal distribution. Class 1 has mean zero and covariance 4 times the identity. Class 2 has mean (a,a,..a) and unit covariance. a = 2/sqrt(20). 2: Type. Classification 3: Origin. Laboratory 4: Instances. 7400 5: Features. 20 6: Classes. 2 7: Missing values. No 8: Header. @relation ring @attribute A1 real [-6879.0, 6285.0] @attribute A2 real [-7141.0, 6921.0] @attribute A3 real [-7734.0, 7611.0] @attribute A4 real [-6627.0, 7149.0] @attribute A5 real [-7184.0, 6383.0] @attribute A6 real [-6946.0, 6743.0] @attribute A7 real [-7781.0, 6285.0] @attribute A8 real [-6882.0, 6357.0] @attribute A9 real [-7184.0, 7487.0] @attribute A10 real [-7232.0, 6757.0] @attribute A11 real [-7803.0, 7208.0] @attribute A12 real [-7395.0, 6791.0] @attribute A13 real [-7096.0, 6403.0] @attribute A14 real [-7472.0, 7261.0] @attribute A15 real [-7342.0, 7372.0] @attribute A16 real [-7121.0, 6905.0] @attribute A17 real [-7163.0, 7175.0] @attribute A18 real [-8778.0, 6896.0] @attribute A19 real [-7554.0, 5726.0] @attribute A20 real [-6722.0, 7627.0] @attribute Class {0, 1} @inputs A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20 @outputs Class