2014-01-04T13:52:04Z
8
80
A Hoeffding tree (VFDT) is an incremental, anytime decision tree induction algorithm
that is capable of learning from massive data streams, assuming that the distribution
generating examples does not change over time. Hoeffding trees exploit the fact that
a small sample can often be enough to choose an optimal splitting attribute. This idea
is supported mathematically by the Hoeffding bound, which quantifies the number
of observations (in our case, examples) needed to estimate some statistics within a
prescribed precision (in our case, the goodness of an attribute).
1
moa.HoeffdingTree
moa.HoeffdingTree
Moa_2014.03
Moa_2014.03_1.0
0
270
public