Question: the table is data ,y is dependent the next four variables are predictors filter value 1 for trainning 0 testing -1 for validation N Percent
the table is data ,y is dependent the next four variables are predictors filter value 1 for trainning 0 testing -1 for validation N Percent Input LayerCovariates x1 x2 x3 x4 Error Function Sum of Squares show how to calculate the folowing out put sse and relative error for each 1,0,-1 group filter
| Training | Sum of Squares Error | 0.36 |
| Relative Error | 0.045 | |
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| Testing | Sum of Squares Error | 0.166 |
| Relative Error | 0.057 | |
| Holdout | Relative Error | 0.237 |
| Dependent y | ||
| rutting | filter | MLP_PredictedValue_A |
| 8.00 | 1 | 7.23 |
| 3.40 | 1 | 3.37 |
| 7.00 | -1 | 6.33 |
| 6.80 | 0 | 6.38 |
| 6.80 | 1 | 6.72 |
| 3.70 | 1 | 3.64 |
| 6.00 | -1 | 5.56 |
| 3.60 | 0 | 3.73 |
| 5.80 | -1 | 5.23 |
| 3.70 | 1 | 3.63 |
| 5.70 | 1 | 5.60 |
| 3.80 | 1 | 3.73 |
| 4.20 | 1 | 4.18 |
| 7.20 | 0 | 7.23 |
| 5.00 | 1 | 5.10 |
| 4.30 | -1 | 4.17 |
| 4.20 | 1 | 4.11 |
| 5.50 | 0 | 5.30 |
| 4.80 | 0 | 4.82 |
| 4.90 | -1 | 4.79 |
| 4.80 | 1 | 4.61 |
| 4.40 | 0 | 4.29 |
| 4.10 | -1 | 4.31 |
| 6.00 | 1 | 6.50 |
| 4.50 | 1 | 4.39 |
| 4.20 | 1 | 4.31 |
| 6.10 | 1 | 6.38 |
| 5.40 | 0 | 5.96 |
| 5.00 | -1 | 5.34 |
| 5.20 | 0 | 5.22 |
| 4.75 | -1 | 5.38 |
| 5.90 | 1 | 6.33 |
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