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Suppose I have a linear model predicting class-membership from a set of predictors. Now, I am going to classify a new observation which has, however, some predictor values missing. How can I deal with such situation? I know there are methods for imputing the missing values but I would like to avoid this and to use only measurements that were really made.

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  • $\begingroup$ Do you know which predictors will be missing? $\endgroup$ – Aksakal Apr 24 '14 at 14:51
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One possible way to deal with this situation without imputation would be to refit the model without the missing predictors.

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