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I'd like to use a random forest for predicting how long a person will stay a customer of our company. One feature I'd like to use is the average age of the customer's kids.

The problem is some customers don't have kids so I can't compute an average. Moreover I can't put 0 because this value means something else: the customer just had his first kid.

How could I handle these missing values in random Forest?

Does it make sense to substitute with a impossible value like -1? If yes is it even better to use a big negative values like - 500?

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    $\begingroup$ Put 0 and make a second feature that is a binary indicator for whether or not the customer has kids. Feature scaling is irrelevant in RF since it just looks for cutpoints, not at the range of values. $\endgroup$ – Sycorax♦ Jul 24 '15 at 17:18
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    $\begingroup$ As feature scaling is indeed irrelevant, could you not code the missing values with -1 and leave the zeros as is? $\endgroup$ – Wouter Jul 24 '15 at 17:47
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In your case I would start with some feature engineering. As mentioned by @user777, start with creating a new variable that indicates whether or not a customer has kids. Then I would look into more details, maybe an indicator with the number of kids. If you have the age of the kids, look into creating age range buckets, or check if a polynomial of age has any relevance.

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