confusion: confusion function
In m-a-r-i-o/aRtistic: Finding Intermediate Mass Black Holes In Star Clusters With Machine Learning
Description
Usage
Arguments
Examples
Description
This function returns a list with the false positive rate (FPR)
and true positive rates (TPR) for a ROC object. The TPR and FPR
are calculated at the furthest point of the ROC curve from the
diagonal identity line, i.e. at the optimal threshold for the
classifier assuming equal cost for false positives and false negatives
Usage
1
confusion(ROC)
Arguments
ROC
ROC object
Examples
1
confusion(ROC)
m-a-r-i-o/aRtistic documentation built on May 7, 2019, 9:37 a.m.
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Description Usage Arguments Examples
Description
This function returns a list with the false positive rate (FPR) and true positive rates (TPR) for a ROC object. The TPR and FPR are calculated at the furthest point of the ROC curve from the diagonal identity line, i.e. at the optimal threshold for the classifier assuming equal cost for false positives and false negatives
Usage
1 | confusion(ROC)
|
Arguments
ROC |
ROC object |
Examples
1 | confusion(ROC)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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