Created
December 2, 2010 20:51
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| Feature: Symbolic regression scoring against x+6 dataset | |
| In order to evaluate how well a Pile script models a given dataset | |
| As a symbolic regression modeler | |
| I want the score of a given script against a dataset to be the RSS value | |
| Scenario: score for a perfect program should be 0.0 | |
| Given the Pile script "x 6.0 +" | |
| And the training data is "x_plus_6.csv" | |
| When I score the script | |
| Then the score should be 0.0 | |
| Scenario: score is summed squared errors | |
| Given the Pile script "x 8.0 +" | |
| And the training data is "x_plus_6.csv" | |
| When I score the script | |
| Then the score should be 36.0 | |
| Scenario: missing return value is important | |
| Given the Pile script "foo bar" | |
| And the training data is "x_plus_6.csv" | |
| When I score the script | |
| Then the score should be close to 10^18 |
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