MilesCranmer commited on
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Fix ordering in docs

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  1. docs/examples.md +3 -3
docs/examples.md CHANGED
@@ -136,7 +136,7 @@ This simple preprocessing step is enough to simplify our tabular dataset,
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  but again, for more structured datasets, you should try the deep learning
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  approach mentioned above.
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- ## 5. Denoising
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  Many datasets, especially in the observational sciences,
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  contain intrinsic noise. PySR is noise robust itself, as it is simply optimizing a loss function,
@@ -170,7 +170,7 @@ print(model)
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  ```
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  If all goes well, you should find that it predicts the correct input equation, without the noise term!
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- ## 6. Additional features
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  For the many other features available in PySR, please
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- read the [Options section](options.md).
 
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  but again, for more structured datasets, you should try the deep learning
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  approach mentioned above.
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+ ## 6. Denoising
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  Many datasets, especially in the observational sciences,
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  contain intrinsic noise. PySR is noise robust itself, as it is simply optimizing a loss function,
 
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  ```
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  If all goes well, you should find that it predicts the correct input equation, without the noise term!
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+ ## 7. Additional features
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  For the many other features available in PySR, please
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+ read the [Options section](options.md).