Research Article
[Retracted] Developing an Efficient Cancer Detection and Prediction Tool Using Convolution Neural Network Integrated with Neural Pattern Recognition
Table 2
Trained and testing parameters for CNN.
| Sample size | Kernel | Mean trained score | Mean test score |
| 30 | 8 | 0.054 | 0.197 | 30 | 16 | 0.032 | 0.167 | 30 | 32 | 0.014 | 0.132 | 30 | 64 | 0.009 | 0.121 | 50 | 8 | 0.072 | 0.196 | 50 | 16 | 0.034 | 0.154 | 50 | 32 | 0.019 | 0.141 | 50 | 64 | 0.011 | 0.132 | 75 | 8 | 0.092 | 0.189 | 75 | 16 | 0.068 | 0.163 | 75 | 32 | 0.031 | 0.145 | 75 | 64 | 0.023 | 0.137 | 85 | 8 | 0.103 | 0.178 | 85 | 16 | 0.087 | 0.156 | 85 | 32 | 0.054 | 0.143 | 85 | 64 | 0.038 | 0.129 | 100 | 8 | 0.128 | 0.172 | 100 | 16 | 0.096 | 0.154 | 100 | 32 | 0.073 | 0.142 | 100 | 64 | 0.046 | 0.121 | 110 | 8 | 0.131 | 0.167 | 110 | 16 | 0.098 | 0.154 | 110 | 32 | 0.081 | 0.136 | 110 | 64 | 0.052 | 0.120 | 125 | 8 | 0.147 | 0.159 | 125 | 16 | 0.100 | 0.141 | 125 | 32 | 0.79 | 0.129 | 125 | 64 | 0.51 | 0.117 |
|
|