Fix auto-select on model failure #998
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prasankh
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| except: | ||
| from sklearn.metrics import r2_score | ||
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| from scipy.stats import linregress |
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Not explicitly, statsmodels is there and it is dependent on scipy.
| nonempty_metrics = {model: metric for model, metric in metrics.items() if metric != {}} | ||
| avg_backtests_metric = {model: sum(value.values()) / len(value.values()) | ||
| for model, value in nonempty_metrics.items()} | ||
| best_model = min(avg_backtests_metric, key=avg_backtests_metric.get) |
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What if the metric is set to accuracy "r-squared"? Do we prevent this?
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The r-squared metric is not present in forecast/schema.yaml file as an allowed optimization metric, so it is not used for selecting the best model. Although it gets calculated when test data is provided only for reporting purpose.
codeloop
approved these changes
Nov 11, 2024
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ODSC-63260
Improved auto-select robustness by selecting the best among successful models.