Changeset 13099 for branches/ClassificationModelComparison
- Timestamp:
- 11/02/15 22:00:14 (9 years ago)
- File:
-
- 1 edited
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branches/ClassificationModelComparison/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/Classification/ClassificationPerformanceMeasures.cs
r13098 r13099 142 142 Add(new Result(TrainingNegativePredictiveValueResultName, "Negative predictive value of the model on the training partition\n(TN/(TN+FN)).", new PercentValue())); 143 143 Add(new Result(TrainingFalsePositiveRateResultName, "The false positive rate is the complement of the true negative rate of the model on the training partition.", new PercentValue())); 144 Add(new Result(TrainingFalseDiscoveryRateResultName, "The false discovery rate is the complement of the positive predictive value of the model on the t estpartition.", new PercentValue()));144 Add(new Result(TrainingFalseDiscoveryRateResultName, "The false discovery rate is the complement of the positive predictive value of the model on the training partition.", new PercentValue())); 145 145 Add(new Result(TrainingF1ScoreResultName, "The F1 score of the model on the training partition.", new DoubleValue())); 146 Add(new Result(TrainingMatthewsCorrelationResultName, "The Matthew 's correlation value of the model on the training partition.", new DoubleValue()));146 Add(new Result(TrainingMatthewsCorrelationResultName, "The Matthews correlation value of the model on the training partition.", new DoubleValue())); 147 147 Add(new Result(TestTruePositiveRateResultName, "Sensitivity/True positive rate of the model on the test partition\n(TP/(TP+FN)).", new PercentValue())); 148 148 Add(new Result(TestTrueNegativeRateResultName, "Specificity/True negative rate of the model on the test partition\n(TN/(FP+TN)).", new PercentValue())); … … 152 152 Add(new Result(TestFalseDiscoveryRateResultName, "The false discovery rate is the complement of the positive predictive value of the model on the test partition.", new PercentValue())); 153 153 Add(new Result(TestF1ScoreResultName, "The F1 score of the model on the test partition.", new DoubleValue())); 154 Add(new Result(TrainingMatthewsCorrelationResultName, "The Matthew 's correlation value of the model on the test partition.", new DoubleValue()));154 Add(new Result(TrainingMatthewsCorrelationResultName, "The Matthews correlation value of the model on the test partition.", new DoubleValue())); 155 155 TrainingTruePositiveRate = double.NaN; 156 156 TrainingTrueNegativeRate = double.NaN;
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