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Anomaly extention Generate ROC seems to mirror FP/FN rate
The dataset contains 1676 items labeled 'true'.
Pls see below a historgram of the scores that uses the label as color. As can be seen it fails to assign a high score to the outliers. This is as aspected because our dataset contains global anomalies. Not the Y-axis is logarithmic for readability purposes.
Below that is the resulting confusion matrix from Generate ROC. It contains 1676 FN's which is explainable if you look at the score.
However it also contains 1676 FP's which is suspicious. I looked in the dataset and there are indeed 1676 predictions with the value "true" so it is not a drawing issue.
I am overlooking something?