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<html> <head> <title> Netlab Reference Manual glmhess </title> </head> <body> <H1> glmhess </H1> <h2> Purpose </h2> Evaluate the Hessian matrix for a generalised linear model. <p><h2> Synopsis </h2> <PRE> h = glmhess(net, x, t) [h, hdata] = glmhess(net, x, t) h = glmhess(net, x, t, hdata) </PRE> <p><h2> Description </h2> <CODE>h = glmhess(net, x, t)</CODE> takes a GLM network data structure <CODE>net</CODE>, a matrix <CODE>x</CODE> of input values, and a matrix <CODE>t</CODE> of target values and returns the full Hessian matrix <CODE>h</CODE> corresponding to the second derivatives of the negative log posterior distribution, evaluated for the current weight and bias values as defined by <CODE>net</CODE>. Note that the target data is not required in the calculation, but is included to make the interface uniform with <CODE>nethess</CODE>. For linear and logistic outputs, the computation is very simple and is done (in effect) in one line in <CODE>glmtrain</CODE>. <p><CODE>[h, hdata] = glmhess(net, x, t)</CODE> returns both the Hessian matrix <CODE>h</CODE> and the contribution <CODE>hdata</CODE> arising from the data dependent term in the Hessian. <p><CODE>h = glmhess(net, x, t, hdata)</CODE> takes a network data structure <CODE>net</CODE>, a matrix <CODE>x</CODE> of input values, and a matrix <CODE>t</CODE> of target values, together with the contribution <CODE>hdata</CODE> arising from the data dependent term in the Hessian, and returns the full Hessian matrix <CODE>h</CODE> corresponding to the second derivatives of the negative log posterior distribution. This version saves computation time if <CODE>hdata</CODE> has already been evaluated for the current weight and bias values. <p><h2> Example </h2> The Hessian matrix is used by <CODE>glmtrain</CODE> to take a Newton step for softmax outputs. <PRE> Hessian = glmhess(net, x, t); deltaw = -gradient*pinv(Hessian); </PRE> <p><h2> See Also </h2> <CODE><a href="glm.htm">glm</a></CODE>, <CODE><a href="glmtrain.htm">glmtrain</a></CODE>, <CODE><a href="hesschek.htm">hesschek</a></CODE>, <CODE><a href="nethess.htm">nethess</a></CODE><hr> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>