The documentation is pretty decent. You could add something like
"trust us it works"... ?
But anyway, I don't trust anything my computer does, and habitually
reach for the print statement so I can check that things are not
going off-the-rails. As they do often.
I'm mightily impressed by the cov
While it's not bad to have more people know the internals of the tree code,
ideally people shouldn't *have* to. Do you have any hints for how
documentation could better serve users to not land in whatever trap you did?
On 15 August 2015 at 16:03, Simon Burton wrote:
>
> My bad. I did something s
My bad. I did something stupid (again).
On the plus side, I now know my way around the internals of
the tree code much better.
Cheers.
On Sat, 15 Aug 2015 14:11:49 +1000
Simon Burton wrote:
>
> Hi,
>
> I am training a DecisionTreeClassifier on samples with a large (500)
> number of feature
Hi,
I am training a DecisionTreeClassifier on samples with a large (500)
number of features. I find that the tree refuses to grow (and so
cannot be used in boosting) unless I remove (zero) some of the
features. This seems strange. Any ideas why? I tried fiddling
with the settings, now delving int
