I was checking [Kaggles Titanic](https://www.kaggle.com/c/titanic/data) problem and a common feature processing is playing with `Parch` (number of parents) and `Sibsp` (number of siblings/spouses).

* First they take it as they come.
* Then they mix the two in `TotalFamily` (Sibsp + Parch)
* Finally they transform the categorical `TotalFamily` in a binary variable `TravelsAlone` (`TotalFamily = 0`)

This seems to improve performance, I'm trying to understand why:

* one variable is better than two? aren't we loosing relations doing this?
* is it because a binary variable is better than a categorical?
* are these good rules of thumb regardless of the algorithm picked (ensembles, svm, etc).

**Please avoid "check for yourself and see" answers**, as I said, after seeing a lot of people doing the same transformations I think there's a rule of thumb somewhere and I'm trying to find it.