[ML] fix bugs with prediction field value settings#55333
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benwtrent merged 3 commits intoelastic:masterfrom Apr 17, 2020
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[ML] fix bugs with prediction field value settings#55333benwtrent merged 3 commits intoelastic:masterfrom
benwtrent merged 3 commits intoelastic:masterfrom
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...rc/main/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/PredictionFieldType.java
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...st/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/PredictionFieldTypeTests.java
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przemekwitek
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Apr 17, 2020
| } | ||
| // Quick check to verify that the string rep is LIKELY a number | ||
| // Still handles the case where it throws and then returns the underlying value | ||
| if (stringRep.charAt(0) == '-' || Character.isDigit(stringRep.charAt(0))) { |
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Could we just drop it and rely solely on parseLong?
Or is this some kind of perf optimization? If so, are you sure it is really faster?
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It is way faster if stringRep is consistently not a number (which could easily be the case). Every call that it is not a number throws an exception, and the JVM has to build a trace.
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This fixes two unreleased bugs: 1. Prediction value type of `number` might show unexpected classes Analytics created models may have class labels like `1, 5, 10` (or some collection of discrete, whole numbers). These labels are passed to the inference model config in the `classification_labels` field. When the predicted value format is `numeric` it should attempt to see if the classification labels are provided and are numeric. If so, use those. If not, use the underlying value. 2. When supplying an update overwrite, inference was losing the default prediction field value. This is because it was not copied over in the copy ctor in the ClassificationConfig.Builder class. closes elastic#55332
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…5394) * [ML] fix bugs with prediction field value settings (#55333) This fixes two unreleased bugs: 1. Prediction value type of `number` might show unexpected classes Analytics created models may have class labels like `1, 5, 10` (or some collection of discrete, whole numbers). These labels are passed to the inference model config in the `classification_labels` field. When the predicted value format is `numeric` it should attempt to see if the classification labels are provided and are numeric. If so, use those. If not, use the underlying value. 2. When supplying an update overwrite, inference was losing the default prediction field value. This is because it was not copied over in the copy ctor in the ClassificationConfig.Builder class. closes #55332
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This fixes two unreleased bugs:
numbermight show unexpected classesAnalytics created models may have class labels like
1, 5, 10(or some collection of discrete, whole numbers). These labels are passed to the inference model config in theclassification_labelsfield.When the predicted value format is
numericit should attempt to see if the classification labels are provided and are numeric. If so, use those. If not, use the underlying value.closes #55332