The evaluation criteria of the three network structures when a threshold of 0.99 is used, for the final test data set created using a uniform distribution of lens model parameters. We also include the results when network structures 1 and 2 are combined.
| . | Structure 1 . | Structure 2 . | Structure 3 . | Avg. Str. 1 + 2 . |
|---|---|---|---|---|
| Accuracy | 0.946 | 0.951 | 0.926 | 0.940 |
| Precision | 0.9985 | 0.9990 | 0.9792 | 0.9999 |
| Recall | 0.893 | 0.903 | 0.871 | 0.880 |
| Fall out | 0.001 38 | 0.000 92 | 0.018 46 | 0.000 06 |
| . | Structure 1 . | Structure 2 . | Structure 3 . | Avg. Str. 1 + 2 . |
|---|---|---|---|---|
| Accuracy | 0.946 | 0.951 | 0.926 | 0.940 |
| Precision | 0.9985 | 0.9990 | 0.9792 | 0.9999 |
| Recall | 0.893 | 0.903 | 0.871 | 0.880 |
| Fall out | 0.001 38 | 0.000 92 | 0.018 46 | 0.000 06 |
The evaluation criteria of the three network structures when a threshold of 0.99 is used, for the final test data set created using a uniform distribution of lens model parameters. We also include the results when network structures 1 and 2 are combined.
| . | Structure 1 . | Structure 2 . | Structure 3 . | Avg. Str. 1 + 2 . |
|---|---|---|---|---|
| Accuracy | 0.946 | 0.951 | 0.926 | 0.940 |
| Precision | 0.9985 | 0.9990 | 0.9792 | 0.9999 |
| Recall | 0.893 | 0.903 | 0.871 | 0.880 |
| Fall out | 0.001 38 | 0.000 92 | 0.018 46 | 0.000 06 |
| . | Structure 1 . | Structure 2 . | Structure 3 . | Avg. Str. 1 + 2 . |
|---|---|---|---|---|
| Accuracy | 0.946 | 0.951 | 0.926 | 0.940 |
| Precision | 0.9985 | 0.9990 | 0.9792 | 0.9999 |
| Recall | 0.893 | 0.903 | 0.871 | 0.880 |
| Fall out | 0.001 38 | 0.000 92 | 0.018 46 | 0.000 06 |
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