Missing Values

As mentioned before, one of the advantages of classification and regression trees is their ability to accommodate missing values. If a response variable is missing, that observation can be excluded from the analysis, or, in the case of classification problem, treated as a new class (e.g., missing) to identify any potential patterns in the loss of information. If explanatory variables are missing, trees can use surrogate variables in their place to determine the split. Alternatively, an observation can be passed to the next node using a variable that is not missing for that observation.

Was this article helpful?

0 0
Solar Power Sensation V2

Solar Power Sensation V2

This is a product all about solar power. Within this product you will get 24 videos, 5 guides, reviews and much more. This product is great for affiliate marketers who is trying to market products all about alternative energy.

Get My Free Ebook


Post a comment