H2O error logistic regression
Hello,
I am a student using RM for my education.
I have a dataset from internet and want to use logistic regression on it but when running the model I get this message: Model training error (H2O) illegal arguments for GLM mode: ERRR of field etc etc.
Does somebody know what i did wrong?
Best regards,
Robert
I am a student using RM for my education.
I have a dataset from internet and want to use logistic regression on it but when running the model I get this message: Model training error (H2O) illegal arguments for GLM mode: ERRR of field etc etc.
Does somebody know what i did wrong?
Best regards,
Robert
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Hello Varun,
Thanks for your help.
I had to take out the numerical to binomial operator, but then it worked.
I also read about the stratified split and understand why this could be better.
Thnk you again.
Best regards,
Robert
Thanks for your help.
I had to take out the numerical to binomial operator, but then it worked.
I also read about the stratified split and understand why this could be better.
Thnk you again.
Best regards,
Robert
Sort by:
1 - 1 of
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Hello @Roeieber
The error implies that you are trying to train that model on a dataset that has a single label. I know you are not really trying to do this, but the data entering into the logistic regression is like that.
Reasons:
1. You did a split validation on data that is highly imbalanced. I recommend you select stratified sampling for this after setting a label role for a column in our data.
2. Also, you made the process a bit complex by adding a set role and numerical to binomial operators after the splitting of data. This is not necessary and also has some issues while encoding numerical to binomial.
I changed the process and attached it. Import it, test it and inform if you need more information.
Hope this helps.
The error implies that you are trying to train that model on a dataset that has a single label. I know you are not really trying to do this, but the data entering into the logistic regression is like that.
Reasons:
1. You did a split validation on data that is highly imbalanced. I recommend you select stratified sampling for this after setting a label role for a column in our data.
2. Also, you made the process a bit complex by adding a set role and numerical to binomial operators after the splitting of data. This is not necessary and also has some issues while encoding numerical to binomial.
I changed the process and attached it. Import it, test it and inform if you need more information.
Hope this helps.
The error implies that you are trying to train that model on a dataset that has a single label. I know you are not really trying to do this, but the data entering into the logistic regression is like that.
Reasons:
1. You did a split validation on data that is highly imbalanced. I recommend you select stratified sampling for this after setting a label role for a column in our data.
2. Also, you made the process a bit complex by adding a set role and numerical to binomial operators after the splitting of data. This is not necessary and also has some issues while encoding numerical to binomial.
I changed the process and attached it. Import it, test it and inform if you need more information.
Hope this helps.