📄 glmderiv.htm
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<html><head><title>Netlab Reference Manual glmderiv</title></head><body><H1> glmderiv</H1><h2>Purpose</h2>Evaluate derivatives of GLM outputs with respect to weights.<p><h2>Synopsis</h2><PRE>g = glmderiv(net, x)</PRE><p><h2>Description</h2><CODE>g = glmderiv(net, x)</CODE> takes a network data structure <CODE>net</CODE> and a matrixof input vectors <CODE>x</CODE> and returns a three-index matrix mat{g} whose <CODE>i</CODE>, <CODE>j</CODE>, <CODE>k</CODE>element contains the derivative of network output <CODE>k</CODE> with respect toweight or bias parameter <CODE>j</CODE> for input pattern <CODE>i</CODE>. The ordering of theweight and bias parameters is defined by <CODE>glmunpak</CODE>.<p><h2>See also</h2><PRE>glm, glmunpak, glmgrad</PRE><p><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)</body></html>⌨️ 快捷键说明
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