How to decide optimal threshold for my classification model from FPR, TPR and threshold
$begingroup$
I am building my model in Python to classify customer in buyer/ non-buyer category. I used mutiple agorithms for this problem and then after evaluation selecting the best out of all.
sklearn package in python gives me an array of FPR,TPR and threshold for all my predicted records.
While analyzing the value of FPR,TPR and threshold I got confused how to interpret threshold value. I am getting threshold value for each record.
For example: My testing dataset consist of 100 records tehn I got array of size 100 for TPR,FPR and threshold.
How to decide the optimium threshold for my model using these values??
from sklearn import metrics
fpr, tpr,threshold = metrics.roc_curve( Y_test, status[:,1])
classification machine-learning-model performance confusion-matrix
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
$endgroup$
bumped to the homepage by Community♦ 15 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I am building my model in Python to classify customer in buyer/ non-buyer category. I used mutiple agorithms for this problem and then after evaluation selecting the best out of all.
sklearn package in python gives me an array of FPR,TPR and threshold for all my predicted records.
While analyzing the value of FPR,TPR and threshold I got confused how to interpret threshold value. I am getting threshold value for each record.
For example: My testing dataset consist of 100 records tehn I got array of size 100 for TPR,FPR and threshold.
How to decide the optimium threshold for my model using these values??
from sklearn import metrics
fpr, tpr,threshold = metrics.roc_curve( Y_test, status[:,1])
classification machine-learning-model performance confusion-matrix
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
$endgroup$
bumped to the homepage by Community♦ 15 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I am building my model in Python to classify customer in buyer/ non-buyer category. I used mutiple agorithms for this problem and then after evaluation selecting the best out of all.
sklearn package in python gives me an array of FPR,TPR and threshold for all my predicted records.
While analyzing the value of FPR,TPR and threshold I got confused how to interpret threshold value. I am getting threshold value for each record.
For example: My testing dataset consist of 100 records tehn I got array of size 100 for TPR,FPR and threshold.
How to decide the optimium threshold for my model using these values??
from sklearn import metrics
fpr, tpr,threshold = metrics.roc_curve( Y_test, status[:,1])
classification machine-learning-model performance confusion-matrix
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
$endgroup$
I am building my model in Python to classify customer in buyer/ non-buyer category. I used mutiple agorithms for this problem and then after evaluation selecting the best out of all.
sklearn package in python gives me an array of FPR,TPR and threshold for all my predicted records.
While analyzing the value of FPR,TPR and threshold I got confused how to interpret threshold value. I am getting threshold value for each record.
For example: My testing dataset consist of 100 records tehn I got array of size 100 for TPR,FPR and threshold.
How to decide the optimium threshold for my model using these values??
from sklearn import metrics
fpr, tpr,threshold = metrics.roc_curve( Y_test, status[:,1])
classification machine-learning-model performance confusion-matrix
classification machine-learning-model performance confusion-matrix
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
asked Sep 20 '18 at 13:48
CodeMaster GoGoCodeMaster GoGo
15810
15810
bumped to the homepage by Community♦ 15 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 15 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
I’m willing to bet that you have a 100 value array for both the ROC and the data by coincidence. You aren’t getting a threshold for each data record but for each threshold evaluated.
At this point, you have to define what ‘optimal’ means in your context. By default (in many R packages at least), sensitivity and specificity are equally weighted, in which case the ‘optimal’ threshold corresponds roughly to the threshold where a 45 degree tangent line intersects the ROC curve. You can choose any threshold you want for a given ROC, depending on how you weight sense/spec. R has a few packages that help compute that; I’d be surprised if Python did not have an equivalent.
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
$endgroup$
add a comment |
Your Answer
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "557"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: false,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: null,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f38544%2fhow-to-decide-optimal-threshold-for-my-classification-model-from-fpr-tpr-and-th%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
I’m willing to bet that you have a 100 value array for both the ROC and the data by coincidence. You aren’t getting a threshold for each data record but for each threshold evaluated.
At this point, you have to define what ‘optimal’ means in your context. By default (in many R packages at least), sensitivity and specificity are equally weighted, in which case the ‘optimal’ threshold corresponds roughly to the threshold where a 45 degree tangent line intersects the ROC curve. You can choose any threshold you want for a given ROC, depending on how you weight sense/spec. R has a few packages that help compute that; I’d be surprised if Python did not have an equivalent.
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
$endgroup$
add a comment |
$begingroup$
I’m willing to bet that you have a 100 value array for both the ROC and the data by coincidence. You aren’t getting a threshold for each data record but for each threshold evaluated.
At this point, you have to define what ‘optimal’ means in your context. By default (in many R packages at least), sensitivity and specificity are equally weighted, in which case the ‘optimal’ threshold corresponds roughly to the threshold where a 45 degree tangent line intersects the ROC curve. You can choose any threshold you want for a given ROC, depending on how you weight sense/spec. R has a few packages that help compute that; I’d be surprised if Python did not have an equivalent.
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
$endgroup$
add a comment |
$begingroup$
I’m willing to bet that you have a 100 value array for both the ROC and the data by coincidence. You aren’t getting a threshold for each data record but for each threshold evaluated.
At this point, you have to define what ‘optimal’ means in your context. By default (in many R packages at least), sensitivity and specificity are equally weighted, in which case the ‘optimal’ threshold corresponds roughly to the threshold where a 45 degree tangent line intersects the ROC curve. You can choose any threshold you want for a given ROC, depending on how you weight sense/spec. R has a few packages that help compute that; I’d be surprised if Python did not have an equivalent.
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
$endgroup$
I’m willing to bet that you have a 100 value array for both the ROC and the data by coincidence. You aren’t getting a threshold for each data record but for each threshold evaluated.
At this point, you have to define what ‘optimal’ means in your context. By default (in many R packages at least), sensitivity and specificity are equally weighted, in which case the ‘optimal’ threshold corresponds roughly to the threshold where a 45 degree tangent line intersects the ROC curve. You can choose any threshold you want for a given ROC, depending on how you weight sense/spec. R has a few packages that help compute that; I’d be surprised if Python did not have an equivalent.
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
answered Sep 20 '18 at 21:05
HEITZHEITZ
63126
63126
add a comment |
add a comment |
Thanks for contributing an answer to Data Science Stack Exchange!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
Use MathJax to format equations. MathJax reference.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fdatascience.stackexchange.com%2fquestions%2f38544%2fhow-to-decide-optimal-threshold-for-my-classification-model-from-fpr-tpr-and-th%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
