Predicting Intent to do X with a confidence score or intent percentage score?
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I have a data set like:
did_purchase action_1_30d action_2_20d action_2_10d ....
False 10 20 100
True ....etc
Where did_purchase shows whether the customer purchased or not, and the columns indicate the volume of actions taken before the purchase (or non-purchase) event.
So, for the first row the customer did 10 of action_1 within 30 days of the purchase event, but didn't purchase in the end.
I have been using sklearn's LogisticRegression to predict the did_purchase false/true, and can get about 89% accuracy, which is nice.
However, I'd like a percentage intent score instead. So it could say user-321 has a 46% chance of purchasing in the next 10 days.
What would be a good algo/approach for this?
logistic-regression
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
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add a comment |
$begingroup$
I have a data set like:
did_purchase action_1_30d action_2_20d action_2_10d ....
False 10 20 100
True ....etc
Where did_purchase shows whether the customer purchased or not, and the columns indicate the volume of actions taken before the purchase (or non-purchase) event.
So, for the first row the customer did 10 of action_1 within 30 days of the purchase event, but didn't purchase in the end.
I have been using sklearn's LogisticRegression to predict the did_purchase false/true, and can get about 89% accuracy, which is nice.
However, I'd like a percentage intent score instead. So it could say user-321 has a 46% chance of purchasing in the next 10 days.
What would be a good algo/approach for this?
logistic-regression
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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$begingroup$
You mention 89% accuracy. What is the distribution of class labels? Is there a class imbalance? If so, accuracy may not be the right metric here.
$endgroup$
– Wes
12 hours ago
$begingroup$
Sorry I meant F1 is 0.89. Class labels were imbalanced 1% Yes - 99% No but I SMOTE'd them
$endgroup$
– LittleBobbyTables
12 hours ago
add a comment |
$begingroup$
I have a data set like:
did_purchase action_1_30d action_2_20d action_2_10d ....
False 10 20 100
True ....etc
Where did_purchase shows whether the customer purchased or not, and the columns indicate the volume of actions taken before the purchase (or non-purchase) event.
So, for the first row the customer did 10 of action_1 within 30 days of the purchase event, but didn't purchase in the end.
I have been using sklearn's LogisticRegression to predict the did_purchase false/true, and can get about 89% accuracy, which is nice.
However, I'd like a percentage intent score instead. So it could say user-321 has a 46% chance of purchasing in the next 10 days.
What would be a good algo/approach for this?
logistic-regression
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have a data set like:
did_purchase action_1_30d action_2_20d action_2_10d ....
False 10 20 100
True ....etc
Where did_purchase shows whether the customer purchased or not, and the columns indicate the volume of actions taken before the purchase (or non-purchase) event.
So, for the first row the customer did 10 of action_1 within 30 days of the purchase event, but didn't purchase in the end.
I have been using sklearn's LogisticRegression to predict the did_purchase false/true, and can get about 89% accuracy, which is nice.
However, I'd like a percentage intent score instead. So it could say user-321 has a 46% chance of purchasing in the next 10 days.
What would be a good algo/approach for this?
logistic-regression
logistic-regression
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
asked 12 hours ago
LittleBobbyTablesLittleBobbyTables
1061
1061
New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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New contributor
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
LittleBobbyTables is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
You mention 89% accuracy. What is the distribution of class labels? Is there a class imbalance? If so, accuracy may not be the right metric here.
$endgroup$
– Wes
12 hours ago
$begingroup$
Sorry I meant F1 is 0.89. Class labels were imbalanced 1% Yes - 99% No but I SMOTE'd them
$endgroup$
– LittleBobbyTables
12 hours ago
add a comment |
$begingroup$
You mention 89% accuracy. What is the distribution of class labels? Is there a class imbalance? If so, accuracy may not be the right metric here.
$endgroup$
– Wes
12 hours ago
$begingroup$
Sorry I meant F1 is 0.89. Class labels were imbalanced 1% Yes - 99% No but I SMOTE'd them
$endgroup$
– LittleBobbyTables
12 hours ago
$begingroup$
You mention 89% accuracy. What is the distribution of class labels? Is there a class imbalance? If so, accuracy may not be the right metric here.
$endgroup$
– Wes
12 hours ago
$begingroup$
You mention 89% accuracy. What is the distribution of class labels? Is there a class imbalance? If so, accuracy may not be the right metric here.
$endgroup$
– Wes
12 hours ago
$begingroup$
Sorry I meant F1 is 0.89. Class labels were imbalanced 1% Yes - 99% No but I SMOTE'd them
$endgroup$
– LittleBobbyTables
12 hours ago
$begingroup$
Sorry I meant F1 is 0.89. Class labels were imbalanced 1% Yes - 99% No but I SMOTE'd them
$endgroup$
– LittleBobbyTables
12 hours ago
add a comment |
1 Answer
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$begingroup$
You could use the probabilities output by LogisticRegressions predict_proba method.
answered 12 hours ago
WesWes
1065
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1 Answer
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1 Answer
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$begingroup$
You could use the probabilities output by LogisticRegressions predict_proba method.
answered 12 hours ago
WesWes
1065
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Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$begingroup$
You could use the probabilities output by LogisticRegressions predict_proba method.
answered 12 hours ago
WesWes
1065
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Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$begingroup$
You could use the probabilities output by LogisticRegressions predict_proba method.
answered 12 hours ago
WesWes
1065
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Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$endgroup$
You could use the probabilities output by LogisticRegressions predict_proba method.
answered 12 hours ago
WesWes
1065
New contributor
Wes is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
answered 12 hours ago
WesWes
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answered 12 hours ago
WesWes
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answered 12 hours ago
WesWes
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$begingroup$
You mention 89% accuracy. What is the distribution of class labels? Is there a class imbalance? If so, accuracy may not be the right metric here.
$endgroup$
– Wes
12 hours ago
$begingroup$
Sorry I meant F1 is 0.89. Class labels were imbalanced 1% Yes - 99% No but I SMOTE'd them
$endgroup$
– LittleBobbyTables
12 hours ago