[ML] Extend default evaluation metrics to all available#63939
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dimitris-athanasiou merged 2 commits intoelastic:masterfrom Oct 21, 2020
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This commit extends the set of default metrics for the data frame analytics evaluation API to all available metrics. The motivation is that if the user skips setting an explicit set of metrics, they get most of the evaluation offering.
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Pinging @elastic/ml-core (:ml) |
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@szabosteve Perhaps it would be worth adding to our docs an explanation about which metrics are included by default. If you agree let's discuss it offline. |
benwtrent
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…#63939) This commit extends the set of default metrics for the data frame analytics evaluation API to all available metrics. The motivation is that if the user skips setting an explicit set of metrics, they get most of the evaluation offering. Backport of elastic#63939
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Oct 21, 2020
This commit extends the set of default metrics for the data frame analytics evaluation API to all available metrics. The motivation is that if the user skips setting an explicit set of metrics, they get most of the evaluation offering.
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| private static List<EvaluationMetric> defaultMetrics() { | ||
| return Arrays.asList(new MeanSquaredError(), new RSquared()); | ||
| return Arrays.asList(new MeanSquaredError(), new RSquared(), new Huber()); |
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Was it on purpose not to include MSLE here? Is it because we cannot set offset automagically for the user?
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It was intentional indeed. The reason is because we cannot calculate MSLE for negative values.
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This commit extends the set of default metrics for the
data frame analytics evaluation API to all available metrics.
The motivation is that if the user skips setting an explicit
set of metrics, they get most of the evaluation offering.