Estimating the accuracy of a model?
$begingroup$
Given that I have a machine learning model.
I evaluated the model over several labeled datasets and acquired the accuracy (or any other metrics) for these datasets.
Now I receive a new dataset without labels. I run the model and got the prediction.
Is there any way to estimate the accuracy of my model on the new dataset?
I was thinking of measuring the similarity of the datasets (in the feature space), then based on the similarity to predict the accuracy of the new dataset. For instance, if the new dataset is not far from the old dataset, the accuracies might be similar.
machine-learning-model
asked 3 hours ago
mommomonthewindmommomonthewind
1012
$endgroup$
add a comment |
$begingroup$
Given that I have a machine learning model.
I evaluated the model over several labeled datasets and acquired the accuracy (or any other metrics) for these datasets.
Now I receive a new dataset without labels. I run the model and got the prediction.
Is there any way to estimate the accuracy of my model on the new dataset?
I was thinking of measuring the similarity of the datasets (in the feature space), then based on the similarity to predict the accuracy of the new dataset. For instance, if the new dataset is not far from the old dataset, the accuracies might be similar.
machine-learning-model
asked 3 hours ago
mommomonthewindmommomonthewind
1012
$endgroup$
add a comment |
$begingroup$
Given that I have a machine learning model.
I evaluated the model over several labeled datasets and acquired the accuracy (or any other metrics) for these datasets.
Now I receive a new dataset without labels. I run the model and got the prediction.
Is there any way to estimate the accuracy of my model on the new dataset?
I was thinking of measuring the similarity of the datasets (in the feature space), then based on the similarity to predict the accuracy of the new dataset. For instance, if the new dataset is not far from the old dataset, the accuracies might be similar.
machine-learning-model
asked 3 hours ago
mommomonthewindmommomonthewind
1012
$endgroup$
Given that I have a machine learning model.
I evaluated the model over several labeled datasets and acquired the accuracy (or any other metrics) for these datasets.
Now I receive a new dataset without labels. I run the model and got the prediction.
Is there any way to estimate the accuracy of my model on the new dataset?
I was thinking of measuring the similarity of the datasets (in the feature space), then based on the similarity to predict the accuracy of the new dataset. For instance, if the new dataset is not far from the old dataset, the accuracies might be similar.
machine-learning-model
machine-learning-model
asked 3 hours ago
mommomonthewindmommomonthewind
1012
asked 3 hours ago
mommomonthewindmommomonthewind
1012
asked 3 hours ago
mommomonthewindmommomonthewind
1012
asked 3 hours ago
mommomonthewindmommomonthewind
1012
asked 3 hours ago
mommomonthewindmommomonthewind
1012
1012
add a comment |
add a comment |
1 Answer
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$begingroup$
I don't get it. You have data with labels and features. And are you using supervised machine learning algorithm. If yours new dataset hasn't labels, you have two options:
- add labels to dataset
- request for another dataset with labels
If you haven't labels you cannot use metrics like accuracy, precision etc because
you don't know what's is TP or TN.
answered 1 hour ago
PawełPaweł
465
$endgroup$
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
I don't get it. You have data with labels and features. And are you using supervised machine learning algorithm. If yours new dataset hasn't labels, you have two options:
- add labels to dataset
- request for another dataset with labels
If you haven't labels you cannot use metrics like accuracy, precision etc because
you don't know what's is TP or TN.
answered 1 hour ago
PawełPaweł
465
$endgroup$
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
add a comment |
$begingroup$
I don't get it. You have data with labels and features. And are you using supervised machine learning algorithm. If yours new dataset hasn't labels, you have two options:
- add labels to dataset
- request for another dataset with labels
If you haven't labels you cannot use metrics like accuracy, precision etc because
you don't know what's is TP or TN.
answered 1 hour ago
PawełPaweł
465
$endgroup$
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
add a comment |
$begingroup$
I don't get it. You have data with labels and features. And are you using supervised machine learning algorithm. If yours new dataset hasn't labels, you have two options:
- add labels to dataset
- request for another dataset with labels
If you haven't labels you cannot use metrics like accuracy, precision etc because
you don't know what's is TP or TN.
answered 1 hour ago
PawełPaweł
465
$endgroup$
I don't get it. You have data with labels and features. And are you using supervised machine learning algorithm. If yours new dataset hasn't labels, you have two options:
- add labels to dataset
- request for another dataset with labels
If you haven't labels you cannot use metrics like accuracy, precision etc because
you don't know what's is TP or TN.
answered 1 hour ago
PawełPaweł
465
answered 1 hour ago
PawełPaweł
465
answered 1 hour ago
PawełPaweł
465
answered 1 hour ago
PawełPaweł
465
465
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
add a comment |
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
$begingroup$
That's why my question is "to estimate", not "to measure". I am asking if there is a technique that estimates (or predicts if you like) the performance of the model if we perform the model on a particular dataset without the label.
$endgroup$
– mommomonthewind
1 hour ago
add a comment |
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