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0

$begingroup$

So I want to perform a predictive model to predict churn.

I have 2 datasets, one with churn and the other without (so I can later perform predictions).

The issue is that I think my Confussion matrix is kinda bad since my target variable is highly unbalanced:

which mostly leads to this confussion matrix:

(Similar values for both logistic regression and decision tree).

This is my workflow:

Is there any way to balance the data? I can't find it in the Orange documentation.

predictive-modeling logistic-regression prediction orange unbalanced-classes

share|improve this question

asked 10 mins ago

Daniel RivasDaniel Rivas

1

New contributor

Daniel Rivas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

0

$begingroup$

So I want to perform a predictive model to predict churn.

I have 2 datasets, one with churn and the other without (so I can later perform predictions).

The issue is that I think my Confussion matrix is kinda bad since my target variable is highly unbalanced:

which mostly leads to this confussion matrix:

(Similar values for both logistic regression and decision tree).

This is my workflow:

Is there any way to balance the data? I can't find it in the Orange documentation.

predictive-modeling logistic-regression prediction orange unbalanced-classes

share|improve this question

asked 10 mins ago

Daniel RivasDaniel Rivas

1

New contributor

Daniel Rivas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

So I want to perform a predictive model to predict churn.

I have 2 datasets, one with churn and the other without (so I can later perform predictions).

The issue is that I think my Confussion matrix is kinda bad since my target variable is highly unbalanced:

which mostly leads to this confussion matrix:

(Similar values for both logistic regression and decision tree).

This is my workflow:

Is there any way to balance the data? I can't find it in the Orange documentation.

predictive-modeling logistic-regression prediction orange unbalanced-classes

share|improve this question

asked 10 mins ago

Daniel RivasDaniel Rivas

1

New contributor

Daniel Rivas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this question

asked 10 mins ago

Daniel RivasDaniel Rivas

1

New contributor

Daniel Rivas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

asked 10 mins ago

Daniel RivasDaniel Rivas

1

New contributor

Daniel Rivas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 10 mins ago

Daniel RivasDaniel Rivas

1

New contributor

Daniel Rivas is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 10 mins ago

Daniel RivasDaniel Rivas

1