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1 <html> | |
2 <head> | |
3 <title> | |
4 Netlab Reference Manual glmerr | |
5 </title> | |
6 </head> | |
7 <body> | |
8 <H1> glmerr | |
9 </H1> | |
10 <h2> | |
11 Purpose | |
12 </h2> | |
13 Evaluate error function for generalized linear model. | |
14 | |
15 <p><h2> | |
16 Synopsis | |
17 </h2> | |
18 <PRE> | |
19 e = glmerr(net, x, t) | |
20 [e, edata, eprior] = glmerr(net, x, t) | |
21 [e, edata, eprior, y, a] = glmerr(net, x, t) | |
22 </PRE> | |
23 | |
24 | |
25 <p><h2> | |
26 Description | |
27 </h2> | |
28 | |
29 <CODE>e = glmerr(net, x, t)</CODE> takes a generalized | |
30 linear model data structure <CODE>net</CODE> together with a matrix <CODE>x</CODE> | |
31 of input vectors and a matrix <CODE>t</CODE> of target vectors, and evaluates | |
32 the error function <CODE>e</CODE>. The choice of error function corresponds | |
33 to the output unit activation function. Each row of <CODE>x</CODE> | |
34 corresponds to one input vector and each row of <CODE>t</CODE> corresponds to | |
35 one target vector. | |
36 | |
37 <p><CODE>[e, edata, eprior, y, a] = glmerr(net, x, t)</CODE> also returns | |
38 the data and prior components of the total error. | |
39 | |
40 <p><CODE>[e, edata, eprior, y, a] = glmerr(net, x)</CODE> also returns a matrix <CODE>y</CODE> | |
41 giving the outputs of the models and a matrix <CODE>a</CODE> | |
42 giving the summed inputs to each output unit, where each row | |
43 corresponds to one pattern. | |
44 | |
45 <p><h2> | |
46 See Also | |
47 </h2> | |
48 <CODE><a href="glm.htm">glm</a></CODE>, <CODE><a href="glmpak.htm">glmpak</a></CODE>, <CODE><a href="glmunpak.htm">glmunpak</a></CODE>, <CODE><a href="glmfwd.htm">glmfwd</a></CODE>, <CODE><a href="glmgrad.htm">glmgrad</a></CODE>, <CODE><a href="glmtrain.htm">glmtrain</a></CODE><hr> | |
49 <b>Pages:</b> | |
50 <a href="index.htm">Index</a> | |
51 <hr> | |
52 <p>Copyright (c) Ian T Nabney (1996-9) | |
53 | |
54 | |
55 </body> | |
56 </html> |