228 CHAPTER 6| IMPLEMENTATIONS: REAL MACHINE LEARNING SCHEMES
where f(x) is the network’s prediction obtained from the output unit and yis
the instance’s class label (in this case, it is assumed to be either 0 or 1). The factor
1/2 is included just for convenience, and will drop out when we start taking
derivatives.
Eyfx=-( ( ))
1
2
2
,
0
0.2
0.4
0.6
0.8
1
-10 -5 0 5 10
(a)
0
0.2
0.4
0.6
0.8
1
-10 -5 0 5 10
(b)
Figure 6.11Step versus sigmoid: (a) step function and (b) sigmoid function.