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Fix PFI issue in binary classification #4587

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Merged
merged 10 commits into from
Jan 8, 2020
Merged

Fix PFI issue in binary classification #4587

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4ed3ca8
Add non-calibrated evaluation to PFI
yaeldMS Dec 18, 2019
fe48872
change to always call EvaluateNonCalibrated
yaeldMS Jan 2, 2020
b6ed4b3
Add non-calibrated evaluation to PFI
yaeldMS Dec 18, 2019
0559fb7
change to always call EvaluateNonCalibrated
yaeldMS Jan 2, 2020
6558551
Add non-calibrated evaluation to PFI
yaeldMS Dec 18, 2019
2d53161
change to always call EvaluateNonCalibrated
yaeldMS Jan 2, 2020
bd2af8e
Add non-calibrated evaluation to PFI
yaeldMS Dec 18, 2019
6e53e5b
Add asserts to unit test
yaeldMS Jan 5, 2020
8bde46b
Remove using statements
yaeldMS Jan 5, 2020
cd7f27c
Remove unused ctor
yaeldMS Jan 7, 2020
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change to always call EvaluateNonCalibrated
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@yaeldMS
yaeldMS committed Jan 5, 2020
commit 2d53161efc9543f50fcd51da1398cd87472154d6
10 changes: 0 additions & 10 deletions src/Microsoft.ML.Data/Evaluators/Metrics/CalibratedBinaryClassificationMetrics.cs
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Expand Up @@ -49,15 +49,5 @@ internal CalibratedBinaryClassificationMetrics(IHost host, DataViewRow overallRe
LogLossReduction = Fetch(BinaryClassifierEvaluator.LogLossReduction);
Entropy = Fetch(BinaryClassifierEvaluator.Entropy);
}

[BestFriend]
internal CalibratedBinaryClassificationMetrics(double auc, double accuracy, double positivePrecision, double positiveRecall,
double negativePrecision, double negativeRecall, double f1Score, double auprc, double logLoss, double logLossReduction, double entropy)
: base(auc, accuracy, positivePrecision, positiveRecall, negativePrecision, negativeRecall, f1Score, auprc)
{
LogLoss = logLoss;
LogLossReduction = logLossReduction;
Entropy = entropy;
}
}
}
43 changes: 0 additions & 43 deletions src/Microsoft.ML.Transforms/PermutationFeatureImportanceExtensions.cs
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Expand Up @@ -146,32 +146,6 @@ public static ImmutableArray<BinaryClassificationMetricsStatistics>
int? numberOfExamplesToUse = null,
int permutationCount = 1) where TModel : class
{
bool isCalibratedModel = false;
var type = predictionTransformer.Model.GetType();
if (type.IsGenericType)
{
var genArgs = type.GetGenericArguments();
if (Utils.Size(genArgs) == 2)
{
var calibratedModelType = typeof(CalibratedModelParametersBase<,>).MakeGenericType(genArgs);
if (calibratedModelType.IsAssignableFrom(type))
isCalibratedModel = true;
}
}
if (isCalibratedModel)
{
return PermutationFeatureImportance<TModel, BinaryClassificationMetrics, BinaryClassificationMetricsStatistics>.GetImportanceMetricsMatrix(
catalog.GetEnvironment(),
predictionTransformer,
data,
() => new BinaryClassificationMetricsStatistics(),
idv => catalog.Evaluate(idv, labelColumnName),
BinaryClassifierDelta,
predictionTransformer.FeatureColumnName,
permutationCount,
useFeatureWeightFilter,
numberOfExamplesToUse);
}
return PermutationFeatureImportance<TModel, BinaryClassificationMetrics, BinaryClassificationMetricsStatistics>.GetImportanceMetricsMatrix(
catalog.GetEnvironment(),
predictionTransformer,
Expand Down Expand Up @@ -199,23 +173,6 @@ private static BinaryClassificationMetrics BinaryClassifierDelta(
auprc: a.AreaUnderPrecisionRecallCurve - b.AreaUnderPrecisionRecallCurve);
}

private static CalibratedBinaryClassificationMetrics CalibratedBinaryClassifierDelta(
CalibratedBinaryClassificationMetrics a, CalibratedBinaryClassificationMetrics b)
{
return new CalibratedBinaryClassificationMetrics(
auc: a.AreaUnderRocCurve - b.AreaUnderRocCurve,
accuracy: a.Accuracy - b.Accuracy,
positivePrecision: a.PositivePrecision - b.PositivePrecision,
positiveRecall: a.PositiveRecall - b.PositiveRecall,
negativePrecision: a.NegativePrecision - b.NegativePrecision,
negativeRecall: a.NegativeRecall - b.NegativeRecall,
f1Score: a.F1Score - b.F1Score,
auprc: a.AreaUnderPrecisionRecallCurve - b.AreaUnderPrecisionRecallCurve,
logLoss: a.LogLoss - b.LogLoss,
logLossReduction: a.LogLossReduction - b.LogLossReduction,
entropy: a.Entropy - b.Entropy);
}

#endregion Binary Classification

#region Multiclass Classification
Expand Down