Dropping attributes leads to better classifier accuracy? (Titanic Set)
I can't say for sure why this happens for this particular data set, but, presumably &quot;Fare&quot; and &quot;Class&quot; are highly correlated. The classifier may do better reasoning about one of them rather than splitting its reasoning across both, as they have mostly the same information.
It's also possible indeed that just knowing whether the person had any family members is most of the useful info, and trying to reason about how many is unhelpful as it is mostly noise that the classifier will overfit.
It's also possible that, given the tiny data set size, you can find lots of ideas that happen to fit the data better, but wouldn't necessarily generalize.