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Had we swapped the assigned labels we would obtain in general a different
value: PE ( p, α, β )= pP E 1 + qPE 0 = + .
Entropy-of-Error criterion:
P 10 ≡ P ( E =1)= p (1 − α ); P 01 ≡ P ( E = 1) = q (1 − β );
(4.51)
To these values we apply formula 4.46. Again, for swapped assignments
one obtains in general a different value.
The three-dimensional functions expressed by formulas (4.46), (4.47), (4.49)
and (4.50) are dicult to mathematically analyze and compare. It turns out
to be more instructive to analyze these functions by considering two categories
of configurations — α = β and α
= β — and inspect the respective values.
Configurations with α = β
For α = β configurations PE doesn't depend on p ( PE =1
α ). All criteria
depend on two parameters alone, p and PE , which facilitates their inspection
as in Fig. 4.12. The behavior of TWO is similar to that of IG .Weobserve
that SEE is concave, symmetric in p but asymmetric in PE ! In conclusion,
SEE displays, just as GI and IG , a desirable concave behavior but more
sensitive to the PE value.
1.4
SEE
1.2
1
1
IG
0.8
0.5
0.6
0.4
0
0
0
0.2
0.2
0.4
p
0
0
p
0.5
0.6
0
0.5
0.8
0.5
PE
PE
1
1
1
1
IG and SEE for α = β (adapted from [152]).
Fig. 4.12
Configurations with α
= β
Figure 4.13 shows the four criteria represented in a ( α, β ) grid for p =0 . 7.
We readily see that IG , TWO and SEE are concave functions whereas PE
is a linear function. Figure 4.14 shows the error PMFs for four specifications
of ( α, β ). Table 4.3 lists the respective criteria values. IG and TWO found
cases 'a' and 'b' to be similar, which seems rather inadequate, whereas both
PE and SEE found 'b' to be an improvement over 'a'. Cases 'b' and 'c'
correspond to those analyzed in [33] to illustrate why PE should not be
used. Note that IG and TWO select 'c' with a decrease of 16% and 11%,
respectively; SEE also selects 'c' and with a more pronounced decrease: 22%.
Therefore, for equal probability of error ( PE =0 . 2 in both cases), SEE also
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