Fuzzy Lattice Reasoning Classifier
FLR Classifier implementation in WEKA
The Fuzzy Lattice Reasoning Classifier uses the notion of Fuzzy Lattices
for creating a Reasoning Environment.
FLR() -
Constructor for class weka.classifiers.misc.FLR
This is needed to get around a bug in Swing <= 1.1 -- Once everyone
is using Swing 1.1.1 or higher just remove this variable and use the
no-arg constructor to DefaultComboBoxModel
Implements the "Farthest First Traversal Algorithm" by
Hochbaum and Shmoys 1985: A best possible heuristic for the
k-center problem, Mathematics of Operations Research, 10(2):180-184,
as cited by Sanjoy Dasgupta "performance guarantees for hierarchical
clustering", colt 2002, sydney
works as a fast simple approximate clusterer
modelled after SimpleKMeans, might be a useful initializer for it
Valid options are:
-N
Specify the number of clusters to generate.
An abstract class for instance filters: objects that take instances
as input, carry out some transformation on the instance and then
output the instance.
This instance filter takes a range of N numeric attributes and replaces
them with N-1 numeric attributes, the values of which are the difference
between consecutive attribute values from the original instance. eg:
Original attribute values 0.1, 0.2, 0.3, 0.1, 0.3
New attribute values 0.1, 0.1, 0.1, -0.2, -0.2
The range of attributes used is taken in numeric order.
Find the K nearest instances to supplied instance if the class is numeric,
or the K nearest Hits (same class) and Misses (K from each of the other
classes) if the class is discrete.