## Missing observations in scored data, no missing data

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Posts: 82

# Missing observations in scored data, no missing data

I am building 4 different logistic models based on 4 different datasets, and then scoring 1 validation dataset with all 4 models to compare the scores.

But for some reason, the scored data is getting different # of observations, even though I know there are no missing values in training or validation data. Is there a reason this would occur?

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‎10-24-2016 05:41 PM
Super User
Posts: 23,776

## Re: Missing observations in scored data, no missing data

If the category isn't in the training data, then yes it would be. It's equivalent to a missing value/category.

If the model is designed for sex=F or sex=M and sex = Unknown appears the model doesn't have a method to score the data and you'll end up with missing values.

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Super User
Posts: 23,776

## Re: Missing observations in scored data, no missing data

When you say missing data, do you mean that all categories are covered in scored data are also covered in training data?

Frequent Contributor
Posts: 82

## Re: Missing observations in scored data, no missing data

Well I guess the scored data set will have more categories than the training data. Is that a problem?
Solution
‎10-24-2016 05:41 PM
Super User
Posts: 23,776

## Re: Missing observations in scored data, no missing data

If the category isn't in the training data, then yes it would be. It's equivalent to a missing value/category.

If the model is designed for sex=F or sex=M and sex = Unknown appears the model doesn't have a method to score the data and you'll end up with missing values.

Frequent Contributor
Posts: 82

## Re: Missing observations in scored data, no missing data

Well I am not sure that is the problem. Some of the scored data match the # of obs in the training data, and some match the # of obs in the validation data.I cant figure it out.

Frequent Contributor
Posts: 82

## Re: Missing observations in scored data, no missing data

So, I see that my socre node has different inputted data. One has the regression train data and one has the validation data, just not sure how that has happened.

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