January 2011
Intermediate to advanced
420 pages
12h 32m
English
Content preview from Practical Applications of Data Mining
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250 Chapter 6 Neural Networks
Next, we continue the process for the second iteration as follows:
Y
Y
Y
Y
f
1
2
3
4
040404
404040
=
−−−
−−−
0004040
404040
1
1
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1
1
1
−−
−−−
×
−
−
=
−
f
4
112
4
12
1
1
1
1−
=
−
−
X
X
X
X
X
X
f
1
2
3
4
5
6
1111
=−−
×
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−−−
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040404
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004040
404040
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At this point, we see that the network converges since there are no state
changes. Since the result is the same as the first training vector (1, –1, 1, –1,
1, –1), the desired output becomes (1, –1, 1, –1), which can be either defined
or interpreted as ...
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