Fix the treatment of LightGbm Evaluation Metric parameters in ML.NET …#3815
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najeeb-kazmi merged 6 commits intodotnet:masterfrom Jun 12, 2019
Merged
Fix the treatment of LightGbm Evaluation Metric parameters in ML.NET …#3815najeeb-kazmi merged 6 commits intodotnet:masterfrom
najeeb-kazmi merged 6 commits intodotnet:masterfrom
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…and make them conform to LightGbm
Ivanidzo4ka
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… ML.NET … (dotnet#3815)" This reverts commit 23332c1. # Conflicts: # test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs
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…and make them conform to LightGbm
Fixes #3761 plus some related issues discovered during investigation
There was a bug in LightGbm
EvaluateMetricTypewhere if a user specifiedEvaluateMetricType.Default, the metric would not get added to the options Dictionary, andLightGbmWrappedTrainingwould throw because of that.Secondly,
EvaluateMetricType.Defaultin LightGbm is supposed to be an empty string "" and LightGbm chooses the default metric according to the problem type when this is specified. This was not present in ML.NET parameter name mappings.EvaluateMetricType.Noneis supposed to be "None" in LightGbm but was "" in ML.NET parameter name mappings.[Update: REVERTED] Third, in ML.NET, the default
EvaluationMetricis set toEvaluateMetricType.Errorfor multiclass,EvaluationMetricType.LogLossfor binary, and so on. This leads to inconsistent behavior from the user's perspective: If a user specifiedEvaluationMetric = EvaluateMetricType.Default, the parameter passed to LightGbm would be the empty string "" but if they do not specifyEvaluationMetricat all, the parameter passed to LightGbm would be Error for multiclass, LogLoss for binary, and so on.This PR does the following:
EvaluationMetricin ML.NET toEvaluationMetricType.Default