R: AUC from pROC package2019 Community Moderator ElectionGetting a low ROC AUC score but a high accuracyObtaining threshold values from a ROC curve3-class AUC calculation in R (pROC package)data.table vs dplyr: can one do something well the other can't or does poorly?Custom AUC in R with different thresholds and binary predictionsHow to calculate multi class classification AUC with labels?R error in calculating AUC value from pROC packageChange default arguments of ROC computation (pROC) in the RFE process (caret) - RHow to compute AUC with ROCR packagexgboost using the auc metric correctlyHow to detect overfitting in xgboost(from test-auc score)
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R: AUC from pROC package
2019 Community Moderator ElectionGetting a low ROC AUC score but a high accuracyObtaining threshold values from a ROC curve3-class AUC calculation in R (pROC package)data.table vs dplyr: can one do something well the other can't or does poorly?Custom AUC in R with different thresholds and binary predictionsHow to calculate multi class classification AUC with labels?R error in calculating AUC value from pROC packageChange default arguments of ROC computation (pROC) in the RFE process (caret) - RHow to compute AUC with ROCR packagexgboost using the auc metric correctlyHow to detect overfitting in xgboost(from test-auc score)
I recently came across pROC package to get AUC. In the help section, they give following example:
library("pROC")
data(aSAH)
auc(aSAH$outcome, aSAH$s100b)
In above, outcome is a factor whereas s100b is numerical.
My question is how does AUC work in this case? What threshold does it apply for s100b? Or it does not matter?
Edit 1
The above code results in AUC = 0.73. How do I know which threshold value was chosen to get this value?
r machine-learning data-science roc auc
asked 2 days ago
chintan schintan s
1,88092951
add a comment |
I recently came across pROC package to get AUC. In the help section, they give following example:
library("pROC")
data(aSAH)
auc(aSAH$outcome, aSAH$s100b)
In above, outcome is a factor whereas s100b is numerical.
My question is how does AUC work in this case? What threshold does it apply for s100b? Or it does not matter?
Edit 1
The above code results in AUC = 0.73. How do I know which threshold value was chosen to get this value?
r machine-learning data-science roc auc
asked 2 days ago
chintan schintan s
1,88092951
Per the docs: "When it is called with two vectors (response, predictor) or a formula (response~predictor) arguments, therocfunction is called and only the AUC is returned." I'm not sure what you mean by thresholds,aucis calculated by default using all thresholds between 0 and 1. You can also check ?roc for details as well.
– zack
2 days ago
@zack thanks for your response. I have added more information. Basically, what determines the output of AUC.
– chintan s
2 days ago
1
You sound a little confused; as @zack says, AUC is calculated across all possible thresholds. Maybe my answer here would be helpful: Getting a low ROC AUC score but a high accuracy.
– desertnaut
2 days ago
add a comment |
I recently came across pROC package to get AUC. In the help section, they give following example:
library("pROC")
data(aSAH)
auc(aSAH$outcome, aSAH$s100b)
In above, outcome is a factor whereas s100b is numerical.
My question is how does AUC work in this case? What threshold does it apply for s100b? Or it does not matter?
Edit 1
The above code results in AUC = 0.73. How do I know which threshold value was chosen to get this value?
r machine-learning data-science roc auc
asked 2 days ago
chintan schintan s
1,88092951
I recently came across pROC package to get AUC. In the help section, they give following example:
library("pROC")
data(aSAH)
auc(aSAH$outcome, aSAH$s100b)
In above, outcome is a factor whereas s100b is numerical.
My question is how does AUC work in this case? What threshold does it apply for s100b? Or it does not matter?
Edit 1
The above code results in AUC = 0.73. How do I know which threshold value was chosen to get this value?
r machine-learning data-science roc auc
r machine-learning data-science roc auc
asked 2 days ago
chintan schintan s
1,88092951
asked 2 days ago
chintan schintan s
1,88092951
edited 2 days ago
chintan s
asked 2 days ago
chintan schintan s
1,88092951
asked 2 days ago
chintan schintan s
1,88092951
asked 2 days ago
chintan schintan s
1,88092951
1,88092951
Per the docs: "When it is called with two vectors (response, predictor) or a formula (response~predictor) arguments, therocfunction is called and only the AUC is returned." I'm not sure what you mean by thresholds,aucis calculated by default using all thresholds between 0 and 1. You can also check ?roc for details as well.
– zack
2 days ago
@zack thanks for your response. I have added more information. Basically, what determines the output of AUC.
– chintan s
2 days ago
1
You sound a little confused; as @zack says, AUC is calculated across all possible thresholds. Maybe my answer here would be helpful: Getting a low ROC AUC score but a high accuracy.
– desertnaut
2 days ago
add a comment |
Per the docs: "When it is called with two vectors (response, predictor) or a formula (response~predictor) arguments, therocfunction is called and only the AUC is returned." I'm not sure what you mean by thresholds,aucis calculated by default using all thresholds between 0 and 1. You can also check ?roc for details as well.
– zack
2 days ago
@zack thanks for your response. I have added more information. Basically, what determines the output of AUC.
– chintan s
2 days ago
1
You sound a little confused; as @zack says, AUC is calculated across all possible thresholds. Maybe my answer here would be helpful: Getting a low ROC AUC score but a high accuracy.
– desertnaut
2 days ago
Per the docs: "When it is called with two vectors (response, predictor) or a formula (response~predictor) arguments, the
roc function is called and only the AUC is returned." I'm not sure what you mean by thresholds, auc is calculated by default using all thresholds between 0 and 1. You can also check ?roc for details as well.– zack
2 days ago
Per the docs: "When it is called with two vectors (response, predictor) or a formula (response~predictor) arguments, the
roc function is called and only the AUC is returned." I'm not sure what you mean by thresholds, auc is calculated by default using all thresholds between 0 and 1. You can also check ?roc for details as well.– zack
2 days ago
@zack thanks for your response. I have added more information. Basically, what determines the output of AUC.
– chintan s
2 days ago
@zack thanks for your response. I have added more information. Basically, what determines the output of AUC.
– chintan s
2 days ago
1
1
You sound a little confused; as @zack says, AUC is calculated across all possible thresholds. Maybe my answer here would be helpful: Getting a low ROC AUC score but a high accuracy.
– desertnaut
2 days ago
You sound a little confused; as @zack says, AUC is calculated across all possible thresholds. Maybe my answer here would be helpful: Getting a low ROC AUC score but a high accuracy.
– desertnaut
2 days ago
add a comment |
1 Answer
1
active
oldest
votes
The AUC in the auc function of pROC is the Area Under the ROC curve. Behind the scenes the function calls the roc function first, and so what you did is equivalent to:
myroc <- roc(aSAH$outcome, aSAH$s100b)
auc(myroc)
The ROC curve is obtained by calculating sensitivity and specificity for all possible thresholds. You can visualize the curve with the plot function, and the AUC is shown in grey:
plot(myroc, auc.polygon=TRUE)
answered 2 days ago
CalimoCalimo
4,42422348
add a comment |
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1 Answer
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oldest
votes
1 Answer
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active
oldest
votes
active
oldest
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The AUC in the auc function of pROC is the Area Under the ROC curve. Behind the scenes the function calls the roc function first, and so what you did is equivalent to:
myroc <- roc(aSAH$outcome, aSAH$s100b)
auc(myroc)
The ROC curve is obtained by calculating sensitivity and specificity for all possible thresholds. You can visualize the curve with the plot function, and the AUC is shown in grey:
plot(myroc, auc.polygon=TRUE)
answered 2 days ago
CalimoCalimo
4,42422348
add a comment |
The AUC in the auc function of pROC is the Area Under the ROC curve. Behind the scenes the function calls the roc function first, and so what you did is equivalent to:
myroc <- roc(aSAH$outcome, aSAH$s100b)
auc(myroc)
The ROC curve is obtained by calculating sensitivity and specificity for all possible thresholds. You can visualize the curve with the plot function, and the AUC is shown in grey:
plot(myroc, auc.polygon=TRUE)
answered 2 days ago
CalimoCalimo
4,42422348
add a comment |
The AUC in the auc function of pROC is the Area Under the ROC curve. Behind the scenes the function calls the roc function first, and so what you did is equivalent to:
myroc <- roc(aSAH$outcome, aSAH$s100b)
auc(myroc)
The ROC curve is obtained by calculating sensitivity and specificity for all possible thresholds. You can visualize the curve with the plot function, and the AUC is shown in grey:
plot(myroc, auc.polygon=TRUE)
answered 2 days ago
CalimoCalimo
4,42422348
The AUC in the auc function of pROC is the Area Under the ROC curve. Behind the scenes the function calls the roc function first, and so what you did is equivalent to:
myroc <- roc(aSAH$outcome, aSAH$s100b)
auc(myroc)
The ROC curve is obtained by calculating sensitivity and specificity for all possible thresholds. You can visualize the curve with the plot function, and the AUC is shown in grey:
plot(myroc, auc.polygon=TRUE)
answered 2 days ago
CalimoCalimo
4,42422348
edited 2 days ago
answered 2 days ago
CalimoCalimo
4,42422348
answered 2 days ago
CalimoCalimo
4,42422348
answered 2 days ago
CalimoCalimo
4,42422348
4,42422348
add a comment |
add a comment |
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Per the docs: "When it is called with two vectors (response, predictor) or a formula (response~predictor) arguments, the
rocfunction is called and only the AUC is returned." I'm not sure what you mean by thresholds,aucis calculated by default using all thresholds between 0 and 1. You can also check ?roc for details as well.– zack
2 days ago
@zack thanks for your response. I have added more information. Basically, what determines the output of AUC.
– chintan s
2 days ago
1
You sound a little confused; as @zack says, AUC is calculated across all possible thresholds. Maybe my answer here would be helpful: Getting a low ROC AUC score but a high accuracy.
– desertnaut
2 days ago