R2_score for GLM #2696
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R2_score for GLM #2696
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aloctavodia
reviewed
Nov 8, 2017
pymc3/stats.py
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| R2_std: standard deviation of the Bayesian R2 | ||
| """ | ||
| e = y_true - y_pred | ||
| var_y_est = np.var(y_pred, 1) |
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This is going to fail if y_predhas dimension 1.
pymc3/stats.py
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| @@ -964,3 +964,33 @@ def bfmi(trace): | |||
| energy = trace['energy'] | |||
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| return np.square(np.diff(energy)).mean() / np.var(energy) | |||
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| def r2_score(y_true, y_pred): | |||
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What about rounding the results by default (maybe 2 decimals) and adding an argument to control this...
pymc3/stats.py
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| var_y_est = np.var(y_pred, 1) | ||
| var_e = np.var(e, 1) | ||
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| r2_median = np.median(var_y_est / (var_y_est + var_e)) |
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maybe you should assign var_y_est / (var_y_est + var_e) to a variable and then use that variable to compute the mean, median and std
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thx |
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LGTM! In your previous PR you had a test, If possible you should add it again. |
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@aloctavodia I didn't make any test in the previous pull request :/ |
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OK, so maybe no test for this PR :-) |
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Thanks @denadai2 |
jordan-melendez
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Feb 6, 2018
* R2_score for GLM * Added round of results and dimension check in r2_score
jordan-melendez
pushed a commit
to jordan-melendez/pymc3
that referenced
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Feb 6, 2018
Add Bayesian R2 PR pymc-devs#2696.
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Fixes #2564.
Ref #2605.