Page 368 - Computational Statistics Handbook with MATLAB

Chapter 9: Statistical Pattern Recognition 357

Subtree − T
3
x1 < 0.031

x2 < 0.51 x2 < 0.58

x1 < 0.49 x1 < 0.5
C− 1 C− 2

C− 1 C− 2C− 2 C− 1

G
9.1
9.1
GU
F F F FI II IG URE GU 9.1 RE RE RE 9.1 5 5 5 5
U
Here is the subtree corresponding to k = 3 from Example 9.12. For this tree, α = 0.03.
reeeUsinganIndepanIndep
Selec
e
BBeestst
th
e
ee
e
an
e
SSeleele
Using
ee
Sele ct cctt nin gg thth eB Be est st T Tr TTrr eeeUsinganIndepIndep eendentndent ndent T Teest st S SSamplampl ample e
Using
ti inin
TTeestst
endent
g
gt
h
Sampl
We first describe the independent test sample case, because it is easier to
understand. The notation that we use is summarized below.
NOTATION - INDEPENDENT TEST SAMPLE METHOD
is the subset of the learning sample L that will be used for building
L 1
the tree.
is the subset of the learning sample L that will be used for testing
L 2
the tree and choosing the best subtree.
2 ()
n is the number of cases in L 2 .
2 ()
n j is the number of observations in L 2 that belong to class ω j .
© 2002 by Chapman & Hall/CRC