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Knowledge Discovery Process and Methods to Enhance Organizational Performance
book

Knowledge Discovery Process and Methods to Enhance Organizational Performance

by Kweku-Muata Osei-Bryson, Corlane Barclay
March 2015
Intermediate to advanced content levelIntermediate to advanced
404 pages
13h 3m
English
Auerbach Publications
Content preview from Knowledge Discovery Process and Methods to Enhance Organizational Performance
Post-Pruning in Decision Tree Induction315
Also, let w
ACC
, w
STAB
, w
DSCPWR
, w
Leaf
, and w
Rule
be the specied nonnegative weights
associated with the accuracy, stability, discriminatory power, leaf simplicity, and
rule simplicity measures, where w
ACC
+w
STAB
+w
DSCPWR
+w
Leaf
+w
Rule
=1.
Our multiobjective, MIP formulation of the DT post-pruning problem with
multiple performance measures can be expressed as follows:
P
SubTree
: Max w
ACC
ACC + w
STAB
STAB
A
+ w
DSCPWR
DSCPWR + w
Leaf
SIMP
Leaf
+
w
Rule
SIMP
Rule
subject to
1:
iIt
x
i
= 1 t I
Leaves
2a:
iI
x
i
[1,LLast]
λ
a
= 0
2b:
[1, LLast]
λ
= 1
2c: λ
1
y
1
2d: λ
y
1
+ y
= 2,. . ., (LLast – 1)
2e: λ
Last
y
(LLast 1)
2f:
[1,(LLast 1)]
y
= 1
2g: y
{0,1}
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Publisher Resources

ISBN: 9781482212365