|
|
MultiPass Instance Learning
-
Version
1.2
MPIL is an instance-based learning system , which
utilizes two models for creating neighborhoods. The
first model places a single neighborhood sphere (based
on Euclidean distance measure) around an instance, and
is in nature similar to the nearest neighbor
classifier, except that it removes redundant
instances. The second model incorporates N radii (one
for each input of an instance). This model also
supports knowledge acquisition in the form of rule
extraction. In a sense, both approaches are similar to
neural networks in that they exploit a very similar
parallelism. MPIL represents a good alternative in
cases were large amounts of data have to be learned
and provides good facilities for storage reduction.
Win32 version.
|