Table III

Neural networks' prediction accuracy and sensitivity analyses with (and without) unsupervised measures

CLVCRVCIVCKV
No.RMSE trainRMSE testRMSE trainRMSE testRMSE trainRMSE testRMSE trainRMSE test
10.126 (0.119)0.112 (0.110)0.189 (0.182)0.184 (0.213)0.144 (0.141)0.167 (0.151)0.142 (0.135)0.149 (0.155)
20.125 (0.123)0.122 (0.108)0.189 (0.182)0.189 (0.218)0.145 (0.147)0.164 (0.116)0.138 (0.138)0.161 (0.125)
30.124 (0.116)0.135 (0.140)0.185 (0.186)0.210 (0.190)0.147 (0.140)0.154 (0.164)0.139 (0.134)0.139 (0.162)
40.128 (0.118)0.115 (0.138)0.185 (0.189)0.194 (0.171)0.148 (0.145)0.132 (0.131)0.139 (0.136)0.150 (0.144)
50.122 (0.118)0.133 (0.135)0.183 (0.191)0.226 (0.194)0.150 (0.141)0.140 (0.168)0.135 (0.136)0.149 (0.151)
60.122 (0.124)0.135 (0.106)0.189 (0.188)0.206 (0.162)0.149 (0.143)0.138 (0.146)0.139 (0.138)0.144 (0.148)
70.122 (0.117)0.146 (0.112)0.186 (0.184)0.225 (0.197)0.147 (0.143)0.157 (0.134)0.143 (0.137)0.109 (0.128)
80.127 (0.118)0.133 (0.125)0.188 (0.182)0.195 (0.233)0.141 (0.142)0.189 (0.171)0.139 (0.138)0.157 (0.117)
90.123 (0.122)0.123 (0.115)0.187 (0.185)0.204 (0.193)0.148 (0.145)0.143 (0.131)0.139 (0.135)0.152 (0.158)
100.126 (0.114)0.127 (0.155)0.186 (0.182)0.206 (0.204)0.145 (0.144)0.173 (0.159)0.140 (0.138)0.143 (0.140)
Mean0.124 (0.119)0.128 (0.124)0.187 (0.185)0.204 (0.197)0.146 (0.143)0.156 (0.147)0.139 (0.137)0.145 (0.143)
 AINIAINIAINIAINI
C0.239 (0.204)61.132 (50.377)0.247 (0.152)67.484 (42.170)0.191 (0.129)56.081 (39.056)0.123 (0.196)27.522 (58.591)
P0.215 (0.243)55.029 (60.119)0.189 (0.16)51.683 (44.488)0.158 (0.246)46.608 (74.664)0.171 (0.154)38.234 (45.977)
Value co-creation opportunities0.157 (0.149)40.129 (36.759)0.198 (0.329)54.211 (91.359)0.311 (0.296)91.599 (89.795)0.258 (0.314)57.510 (93.733)
Engagement0.390 (0.404)100.000 (100.000)0.366 (0.360)100.000 (100.000)0.340 (0.329)100.000 (100.000)0.448 (0.335)100.000 (100.000)
[ViewLarge]
This Feature Is Available To Subscribers Only

or Create an Account

Close Modal
Close Modal