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< div class = "headertitle" > < div class = "title" > adaline_learning.c File Reference< / div > < / div >
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< p > < a href = "https://en.wikipedia.org/wiki/ADALINE" target = "_blank" > Adaptive Linear Neuron (ADALINE)< / a > implementation
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< a href = "#details" > More...< / a > < / p >
< div class = "textblock" > < code > #include < assert.h> < / code > < br / >
< code > #include < limits.h> < / code > < br / >
< code > #include < math.h> < / code > < br / >
< code > #include < stdbool.h> < / code > < br / >
< code > #include < stdio.h> < / code > < br / >
< code > #include < stdlib.h> < / code > < br / >
< code > #include < time.h> < / code > < br / >
< / div > < div class = "textblock" > < div class = "dynheader" >
Include dependency graph for adaline_learning.c:< / div >
< div class = "dyncontent" >
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< div class = "center" > < iframe scrolling = "no" frameborder = "0" src = "../../d9/dcc/adaline__learning_8c__incl.svg" width = "603" height = "126" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe >
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Data Structures< / h2 > < / td > < / tr >
< tr class = "memitem:" > < td class = "memItemLeft" align = "right" valign = "top" > struct   < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a > < / td > < / tr >
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< tr class = "memdesc:" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > structure to hold adaline model parameters < a href = "../../d2/daa/structadaline.html#details" > More...< / a > < br / > < / td > < / tr >
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< tr class = "separator:" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< / table > < table class = "memberdecls" >
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Macros< / h2 > < / td > < / tr >
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< tr class = "memitem:ga555ba960994e9bccb2029764588f694f" > < td class = "memItemLeft" align = "right" valign = "top" >
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#define  < / td > < td class = "memItemRight" valign = "bottom" > < b > MAX_ADALINE_ITER< / b >       500< / td > < / tr >
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< tr class = "memdesc:ga555ba960994e9bccb2029764588f694f" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Maximum number of iterations to learn. < br / > < / td > < / tr >
< tr class = "separator:ga555ba960994e9bccb2029764588f694f" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:gab4d49d73dec94c092b7ffadba55fb020" > < td class = "memItemLeft" align = "right" valign = "top" >
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#define  < / td > < td class = "memItemRight" valign = "bottom" > < b > ADALINE_ACCURACY< / b >       1e-5< / td > < / tr >
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< tr class = "memdesc:gab4d49d73dec94c092b7ffadba55fb020" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > convergence accuracy \(=1\times10^{-5}\) < br / > < / td > < / tr >
< tr class = "separator:gab4d49d73dec94c092b7ffadba55fb020" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< / table > < table class = "memberdecls" >
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Functions< / h2 > < / td > < / tr >
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< tr class = "memitem:gacd88962c5f6341e43cbc69b4a7d3485b" > < td class = "memItemLeft" align = "right" valign = "top" > struct < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a >   < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b" > new_adaline< / a > (const int num_features, const double eta)< / td > < / tr >
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< tr class = "memdesc:gacd88962c5f6341e43cbc69b4a7d3485b" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Default constructor. < br / > < / td > < / tr >
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< tr class = "separator:gacd88962c5f6341e43cbc69b4a7d3485b" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:ga6f35caa3084772cc126ac7b20f67f665" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665" > delete_adaline< / a > (struct < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a > *ada)< / td > < / tr >
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< tr class = "memdesc:ga6f35caa3084772cc126ac7b20f67f665" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > delete dynamically allocated memory < br / > < / td > < / tr >
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< tr class = "separator:ga6f35caa3084772cc126ac7b20f67f665" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:ga43576566b020c4157d4fb28f0dd45cfa" > < td class = "memItemLeft" align = "right" valign = "top" > int  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#ga43576566b020c4157d4fb28f0dd45cfa" > adaline_activation< / a > (double x)< / td > < / tr >
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< tr class = "memdesc:ga43576566b020c4157d4fb28f0dd45cfa" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > < a href = "https://en.wikipedia.org/wiki/Heaviside_step_function" target = "_blank" > Heaviside activation function< / a > < img src = "https://upload.wikimedia.org/wikipedia/commons/d/d9/Dirac_distribution_CDF.svg" alt = "" style = "pointer-events: none;" width = "200px" class = "inline" / > < br / > < / td > < / tr >
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< tr class = "separator:ga43576566b020c4157d4fb28f0dd45cfa" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:gadb1a7acb555ad62daaf3806bf2fed036" > < td class = "memItemLeft" align = "right" valign = "top" > char *  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (const struct < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a > *ada)< / td > < / tr >
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< tr class = "memdesc:gadb1a7acb555ad62daaf3806bf2fed036" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Operator to print the weights of the model. < br / > < / td > < / tr >
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< tr class = "separator:gadb1a7acb555ad62daaf3806bf2fed036" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:gac70b578aee679005fd336073969c3d94" > < td class = "memItemLeft" align = "right" valign = "top" > int  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94" > adaline_predict< / a > (struct < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a > *ada, const double *x, double *out)< / td > < / tr >
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< tr class = "memdesc:gac70b578aee679005fd336073969c3d94" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > predict the output of the model for given set of features < br / > < / td > < / tr >
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< tr class = "separator:gac70b578aee679005fd336073969c3d94" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:ga20d3642e0a87f36fdb7bf91b023cd166" > < td class = "memItemLeft" align = "right" valign = "top" > double  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#ga20d3642e0a87f36fdb7bf91b023cd166" > adaline_fit_sample< / a > (struct < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a > *ada, const double *x, const int y)< / td > < / tr >
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< tr class = "memdesc:ga20d3642e0a87f36fdb7bf91b023cd166" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Update the weights of the model using supervised learning for one feature vector. < br / > < / td > < / tr >
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< tr class = "separator:ga20d3642e0a87f36fdb7bf91b023cd166" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:gaa52120912e32d2893fe1c6d78da5befd" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd" > adaline_fit< / a > (struct < a class = "el" href = "../../d2/daa/structadaline.html" > adaline< / a > *ada, double **X, const int *y, const int N)< / td > < / tr >
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< tr class = "memdesc:gaa52120912e32d2893fe1c6d78da5befd" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Update the weights of the model using supervised learning for an array of vectors. < br / > < / td > < / tr >
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< tr class = "separator:gaa52120912e32d2893fe1c6d78da5befd" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:ab4ecb3accf5d9e0263087e7265bbe3a9" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../dd/d8c/adaline__learning_8c.html#ab4ecb3accf5d9e0263087e7265bbe3a9" > test1< / a > (double eta)< / td > < / tr >
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< tr class = "memdesc:ab4ecb3accf5d9e0263087e7265bbe3a9" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > test function to predict points in a 2D coordinate system above the line \(x=y\) as +1 and others as -1. < br / > < / td > < / tr >
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< tr class = "separator:ab4ecb3accf5d9e0263087e7265bbe3a9" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:a05cc9a0acb524fde727a4d7b4a747ee6" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../dd/d8c/adaline__learning_8c.html#a05cc9a0acb524fde727a4d7b4a747ee6" > test2< / a > (double eta)< / td > < / tr >
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< tr class = "memdesc:a05cc9a0acb524fde727a4d7b4a747ee6" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > test function to predict points in a 2D coordinate system above the line \(x+3y=-1\) as +1 and others as -1. < br / > < / td > < / tr >
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< tr class = "separator:a05cc9a0acb524fde727a4d7b4a747ee6" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< tr class = "memitem:a3f37b9f073f7e57fd0b39d70718af1b1" > < td class = "memItemLeft" align = "right" valign = "top" > void  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../dd/d8c/adaline__learning_8c.html#a3f37b9f073f7e57fd0b39d70718af1b1" > test3< / a > (double eta)< / td > < / tr >
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< tr class = "memdesc:a3f37b9f073f7e57fd0b39d70718af1b1" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > test function to predict points in a 3D coordinate system lying within the sphere of radius 1 and centre at origin as +1 and others as -1. < br / > < / td > < / tr >
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< tr class = "separator:a3f37b9f073f7e57fd0b39d70718af1b1" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
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< tr class = "memitem:a3c04138a5bfe5d72780bb7e82a18e627" > < td class = "memItemLeft" align = "right" valign = "top" > int  < / td > < td class = "memItemRight" valign = "bottom" > < a class = "el" href = "../../dd/d8c/adaline__learning_8c.html#a3c04138a5bfe5d72780bb7e82a18e627" > main< / a > (int argc, char **argv)< / td > < / tr >
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< tr class = "memdesc:a3c04138a5bfe5d72780bb7e82a18e627" > < td class = "mdescLeft" >   < / td > < td class = "mdescRight" > Main function. < br / > < / td > < / tr >
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< tr class = "separator:a3c04138a5bfe5d72780bb7e82a18e627" > < td class = "memSeparator" colspan = "2" >   < / td > < / tr >
< / table >
< a name = "details" id = "details" > < / a > < h2 class = "groupheader" > Detailed Description< / h2 >
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< div class = "textblock" > < p > < a href = "https://en.wikipedia.org/wiki/ADALINE" target = "_blank" > Adaptive Linear Neuron (ADALINE)< / a > implementation < / p >
< p > < img src = "https://upload.wikimedia.org/wikipedia/commons/b/be/Adaline_flow_chart.gif" alt = "" width = "200px" class = "inline" / > < a href = "https://commons.wikimedia.org/wiki/File:Adaline_flow_chart.gif" target = "_blank" > source< / a > ADALINE is one of the first and simplest single layer artificial neural network. The algorithm essentially implements a linear function < / p > < p class = "formulaDsp" >
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\[ f\left(x_0,x_1,x_2,\ldots\right) =
\sum_j x_jw_j+\theta
\]
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< / p >
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< p > where \(x_j\) are the input features of a sample, \(w_j\) are the coefficients of the linear function and \(\theta\) is a constant. If we know the \(w_j\), then for any given set of features, \(y\) can be computed. Computing the \(w_j\) is a supervised learning algorithm wherein a set of features and their corresponding outputs are given and weights are computed using stochastic gradient descent method. < / p > < dl class = "section author" > < dt > Author< / dt > < dd > < a href = "https://github.com/kvedala" target = "_blank" > Krishna Vedala< / a > < / dd > < / dl >
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< / div > < h2 class = "groupheader" > Function Documentation< / h2 >
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< a id = "a3c04138a5bfe5d72780bb7e82a18e627" name = "a3c04138a5bfe5d72780bb7e82a18e627" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#a3c04138a5bfe5d72780bb7e82a18e627" > ◆   < / a > < / span > main()< / h2 >
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< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > int main < / td >
< td > (< / td >
< td class = "paramtype" > int  < / td >
< td class = "paramname" > < em > argc< / em > , < / td >
< / tr >
< tr >
< td class = "paramkey" > < / td >
< td > < / td >
< td class = "paramtype" > char **  < / td >
< td class = "paramname" > < em > argv< / em >   < / td >
< / tr >
< tr >
< td > < / td >
< td > )< / td >
< td > < / td > < td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
< p > Main function. < / p >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 399< / span > {< / div >
< div class = "line" > < span class = "lineno" > 400< / span > srand(time(NULL)); < span class = "comment" > // initialize random number generator< / span > < / div >
< div class = "line" > < span class = "lineno" > 401< / span > < / div >
< div class = "line" > < span class = "lineno" > 402< / span > < span class = "keywordtype" > double< / span > eta = 0.1; < span class = "comment" > // default value of eta< / span > < / div >
< div class = "line" > < span class = "lineno" > 403< / span > < span class = "keywordflow" > if< / span > (argc == 2) < span class = "comment" > // read eta value from commandline argument if present< / span > < / div >
< div class = "line" > < span class = "lineno" > 404< / span > eta = strtof(argv[1], NULL);< / div >
< div class = "line" > < span class = "lineno" > 405< / span > < / div >
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< div class = "line" > < span class = "lineno" > 406< / span > < a class = "code hl_function" href = "../../d2/df6/kohonen__som__topology_8c.html#a1440a7779ac56f47a3f355ce4a8c7da0" > test1< / a > (eta);< / div >
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< div class = "line" > < span class = "lineno" > 407< / span > < / div >
< div class = "line" > < span class = "lineno" > 408< / span > printf(< span class = "stringliteral" > " Press ENTER to continue...\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 409< / span > getchar();< / div >
< div class = "line" > < span class = "lineno" > 410< / span > < / div >
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< div class = "line" > < span class = "lineno" > 411< / span > < a class = "code hl_function" href = "../../d6/d76/k__means__clustering_8c.html#a0283886819c7c140a023582b7269e2d0" > test2< / a > (eta);< / div >
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< div class = "line" > < span class = "lineno" > 412< / span > < / div >
< div class = "line" > < span class = "lineno" > 413< / span > printf(< span class = "stringliteral" > " Press ENTER to continue...\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 414< / span > getchar();< / div >
< div class = "line" > < span class = "lineno" > 415< / span > < / div >
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< div class = "line" > < span class = "lineno" > 416< / span > < a class = "code hl_function" href = "../../d2/df6/kohonen__som__topology_8c.html#a6d0455dd5c30adda100e95f0423c786e" > test3< / a > (eta);< / div >
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< div class = "line" > < span class = "lineno" > 417< / span > < / div >
< div class = "line" > < span class = "lineno" > 418< / span > < span class = "keywordflow" > return< / span > 0;< / div >
< div class = "line" > < span class = "lineno" > 419< / span > }< / div >
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< div class = "ttc" id = "ak__means__clustering_8c_html_a0283886819c7c140a023582b7269e2d0" > < div class = "ttname" > < a href = "../../d6/d76/k__means__clustering_8c.html#a0283886819c7c140a023582b7269e2d0" > test2< / a > < / div > < div class = "ttdeci" > void test2()< / div > < div class = "ttdef" > < b > Definition:< / b > k_means_clustering.c:356< / div > < / div >
< div class = "ttc" id = "akohonen__som__topology_8c_html_a1440a7779ac56f47a3f355ce4a8c7da0" > < div class = "ttname" > < a href = "../../d2/df6/kohonen__som__topology_8c.html#a1440a7779ac56f47a3f355ce4a8c7da0" > test1< / a > < / div > < div class = "ttdeci" > void test1()< / div > < div class = "ttdoc" > Test that creates a random set of points distributed in four clusters in 2D space and trains an SOM t...< / div > < div class = "ttdef" > < b > Definition:< / b > kohonen_som_topology.c:406< / div > < / div >
< div class = "ttc" id = "akohonen__som__topology_8c_html_a6d0455dd5c30adda100e95f0423c786e" > < div class = "ttname" > < a href = "../../d2/df6/kohonen__som__topology_8c.html#a6d0455dd5c30adda100e95f0423c786e" > test3< / a > < / div > < div class = "ttdeci" > void test3()< / div > < div class = "ttdoc" > Test that creates a random set of points distributed in eight clusters in 3D space and trains an SOM ...< / div > < div class = "ttdef" > < b > Definition:< / b > kohonen_som_topology.c:609< / div > < / div >
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< / div > <!-- fragment --> < div class = "dynheader" >
Here is the call graph for this function:< / div >
< div class = "dyncontent" >
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< div class = "center" > < div class = "zoom" > < iframe scrolling = "no" frameborder = "0" src = "../../dd/d8c/adaline__learning_8c_a3c04138a5bfe5d72780bb7e82a18e627_cgraph.svg" width = "100%" height = "600" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe > < / div >
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< / div >
< / div >
< / div >
< / div >
< a id = "ab4ecb3accf5d9e0263087e7265bbe3a9" name = "ab4ecb3accf5d9e0263087e7265bbe3a9" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#ab4ecb3accf5d9e0263087e7265bbe3a9" > ◆   < / a > < / span > test1()< / h2 >
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< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > void test1 < / td >
< td > (< / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > eta< / em > < / td > < td > )< / td >
< td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
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< p > test function to predict points in a 2D coordinate system above the line \(x=y\) as +1 and others as -1. < / p >
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< p > Note that each point is defined by 2 values or 2 features. < / p > < dl class = "params" > < dt > Parameters< / dt > < dd >
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< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > eta< / td > < td > learning rate (optional, default=0.01) < / td > < / tr >
< / table >
< / dd >
< / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 226< / span > {< / div >
< div class = "line" > < span class = "lineno" > 227< / span > < span class = "keyword" > struct < / span > < a class = "code hl_struct" href = "../../d2/daa/structadaline.html" > adaline< / a > ada = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b" > new_adaline< / a > (2, < a class = "code hl_variable" href = "../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2" > eta< / a > ); < span class = "comment" > // 2 features< / span > < / div >
< div class = "line" > < span class = "lineno" > 228< / span > < / div >
< div class = "line" > < span class = "lineno" > 229< / span > < span class = "keyword" > const< / span > < span class = "keywordtype" > int< / span > N = 10; < span class = "comment" > // number of sample points< / span > < / div >
< div class = "line" > < span class = "lineno" > 230< / span > < span class = "keyword" > const< / span > < span class = "keywordtype" > double< / span > saved_X[10][2] = {{0, 1}, {1, -2}, {2, 3}, {3, -1},< / div >
< div class = "line" > < span class = "lineno" > 231< / span > {4, 1}, {6, -5}, {-7, -3}, {-8, 5},< / div >
< div class = "line" > < span class = "lineno" > 232< / span > {-9, 2}, {-10, -15}};< / div >
< div class = "line" > < span class = "lineno" > 233< / span > < / div >
< div class = "line" > < span class = "lineno" > 234< / span > < span class = "keywordtype" > double< / span > **X = (< span class = "keywordtype" > double< / span > **)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (N * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > double< / span > *));< / div >
< div class = "line" > < span class = "lineno" > 235< / span > < span class = "keyword" > const< / span > < span class = "keywordtype" > int< / span > Y[10] = {1, -1, 1, -1, -1,< / div >
< div class = "line" > < span class = "lineno" > 236< / span > -1, 1, 1, 1, -1}; < span class = "comment" > // corresponding y-values< / span > < / div >
< div class = "line" > < span class = "lineno" > 237< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++)< / div >
< div class = "line" > < span class = "lineno" > 238< / span > {< / div >
< div class = "line" > < span class = "lineno" > 239< / span > X[i] = (< span class = "keywordtype" > double< / span > *)saved_X[i];< / div >
< div class = "line" > < span class = "lineno" > 240< / span > }< / div >
< div class = "line" > < span class = "lineno" > 241< / span > < / div >
< div class = "line" > < span class = "lineno" > 242< / span > printf(< span class = "stringliteral" > " ------- Test 1 -------\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 243< / span > printf(< span class = "stringliteral" > " Model before fit: %s\n" < / span > , < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (& ada));< / div >
< div class = "line" > < span class = "lineno" > 244< / span > < / div >
< div class = "line" > < span class = "lineno" > 245< / span > < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd" > adaline_fit< / a > (& ada, X, Y, N);< / div >
< div class = "line" > < span class = "lineno" > 246< / span > printf(< span class = "stringliteral" > " Model after fit: %s\n" < / span > , < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (& ada));< / div >
< div class = "line" > < span class = "lineno" > 247< / span > < / div >
< div class = "line" > < span class = "lineno" > 248< / span > < span class = "keywordtype" > double< / span > test_x[] = {5, -3};< / div >
< div class = "line" > < span class = "lineno" > 249< / span > < span class = "keywordtype" > int< / span > pred = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94" > adaline_predict< / a > (& ada, test_x, NULL);< / div >
< div class = "line" > < span class = "lineno" > 250< / span > printf(< span class = "stringliteral" > " Predict for x=(5,-3): % d\n" < / span > , pred);< / div >
< div class = "line" > < span class = "lineno" > 251< / span > assert(pred == -1);< / div >
< div class = "line" > < span class = "lineno" > 252< / span > printf(< span class = "stringliteral" > " ...passed\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 253< / span > < / div >
< div class = "line" > < span class = "lineno" > 254< / span > < span class = "keywordtype" > double< / span > test_x2[] = {5, 8};< / div >
< div class = "line" > < span class = "lineno" > 255< / span > pred = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94" > adaline_predict< / a > (& ada, test_x2, NULL);< / div >
< div class = "line" > < span class = "lineno" > 256< / span > printf(< span class = "stringliteral" > " Predict for x=(5, 8): % d\n" < / span > , pred);< / div >
< div class = "line" > < span class = "lineno" > 257< / span > assert(pred == 1);< / div >
< div class = "line" > < span class = "lineno" > 258< / span > printf(< span class = "stringliteral" > " ...passed\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 259< / span > < / div >
< div class = "line" > < span class = "lineno" > 260< / span > < span class = "comment" > // for (int i = 0; i < N; i++)< / span > < / div >
< div class = "line" > < span class = "lineno" > 261< / span > < span class = "comment" > // free(X[i]);< / span > < / div >
< div class = "line" > < span class = "lineno" > 262< / span > < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (X);< / div >
< div class = "line" > < span class = "lineno" > 263< / span > < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665" > delete_adaline< / a > (& ada);< / div >
< div class = "line" > < span class = "lineno" > 264< / span > }< / div >
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< div class = "ttc" id = "agroup__adaline_html_ga6f35caa3084772cc126ac7b20f67f665" > < div class = "ttname" > < a href = "../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665" > delete_adaline< / a > < / div > < div class = "ttdeci" > void delete_adaline(struct adaline *ada)< / div > < div class = "ttdoc" > delete dynamically allocated memory< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:89< / div > < / div >
< div class = "ttc" id = "agroup__adaline_html_gaa52120912e32d2893fe1c6d78da5befd" > < div class = "ttname" > < a href = "../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd" > adaline_fit< / a > < / div > < div class = "ttdeci" > void adaline_fit(struct adaline *ada, double **X, const int *y, const int N)< / div > < div class = "ttdoc" > Update the weights of the model using supervised learning for an array of vectors.< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:184< / div > < / div >
< div class = "ttc" id = "agroup__adaline_html_gac70b578aee679005fd336073969c3d94" > < div class = "ttname" > < a href = "../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94" > adaline_predict< / a > < / div > < div class = "ttdeci" > int adaline_predict(struct adaline *ada, const double *x, double *out)< / div > < div class = "ttdoc" > predict the output of the model for given set of features< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:136< / div > < / div >
< div class = "ttc" id = "agroup__adaline_html_gacd88962c5f6341e43cbc69b4a7d3485b" > < div class = "ttname" > < a href = "../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b" > new_adaline< / a > < / div > < div class = "ttdeci" > struct adaline new_adaline(const int num_features, const double eta)< / div > < div class = "ttdoc" > Default constructor.< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:59< / div > < / div >
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< div class = "ttc" id = "agroup__adaline_html_gadb1a7acb555ad62daaf3806bf2fed036" > < div class = "ttname" > < a href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > < / div > < div class = "ttdeci" > char * adaline_get_weights_str(const struct adaline *ada)< / div > < div class = "ttdoc" > Operator to print the weights of the model.< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:112< / div > < / div >
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< div class = "ttc" id = "amalloc__dbg_8h_html_a725f50ecaf1959d96de79b36b4788fee" > < div class = "ttname" > < a href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > < / div > < div class = "ttdeci" > #define malloc(bytes)< / div > < div class = "ttdoc" > This macro replace the standard malloc function with malloc_dbg.< / div > < div class = "ttdef" > < b > Definition:< / b > malloc_dbg.h:18< / div > < / div >
< div class = "ttc" id = "amalloc__dbg_8h_html_a9cc854374299a1dd933bf62029761768" > < div class = "ttname" > < a href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > < / div > < div class = "ttdeci" > #define free(ptr)< / div > < div class = "ttdoc" > This macro replace the standard free function with free_dbg.< / div > < div class = "ttdef" > < b > Definition:< / b > malloc_dbg.h:26< / div > < / div >
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< div class = "ttc" id = "astructadaline_html" > < div class = "ttname" > < a href = "../../d2/daa/structadaline.html" > adaline< / a > < / div > < div class = "ttdoc" > structure to hold adaline model parameters< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:44< / div > < / div >
< div class = "ttc" id = "astructadaline_html_a85dbd7cce6195d11ebb388220b96bde2" > < div class = "ttname" > < a href = "../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2" > adaline::eta< / a > < / div > < div class = "ttdeci" > double eta< / div > < div class = "ttdoc" > learning rate of the algorithm< / div > < div class = "ttdef" > < b > Definition:< / b > adaline_learning.c:45< / div > < / div >
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< / div > <!-- fragment --> < div class = "dynheader" >
Here is the call graph for this function:< / div >
< div class = "dyncontent" >
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< div class = "center" > < div class = "zoom" > < iframe scrolling = "no" frameborder = "0" src = "../../dd/d8c/adaline__learning_8c_ab4ecb3accf5d9e0263087e7265bbe3a9_cgraph.svg" width = "100%" height = "478" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe > < / div >
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< / div >
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< / div >
< / div >
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< a id = "a05cc9a0acb524fde727a4d7b4a747ee6" name = "a05cc9a0acb524fde727a4d7b4a747ee6" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#a05cc9a0acb524fde727a4d7b4a747ee6" > ◆   < / a > < / span > test2()< / h2 >
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< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > void test2 < / td >
< td > (< / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > eta< / em > < / td > < td > )< / td >
< td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
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< p > test function to predict points in a 2D coordinate system above the line \(x+3y=-1\) as +1 and others as -1. < / p >
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< p > Note that each point is defined by 2 values or 2 features. The function will create random sample points for training and test purposes. < / p > < dl class = "params" > < dt > Parameters< / dt > < dd >
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< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > eta< / td > < td > learning rate (optional, default=0.01) < / td > < / tr >
< / table >
< / dd >
< / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 274< / span > {< / div >
< div class = "line" > < span class = "lineno" > 275< / span > < span class = "keyword" > struct < / span > < a class = "code hl_struct" href = "../../d2/daa/structadaline.html" > adaline< / a > ada = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b" > new_adaline< / a > (2, < a class = "code hl_variable" href = "../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2" > eta< / a > ); < span class = "comment" > // 2 features< / span > < / div >
< div class = "line" > < span class = "lineno" > 276< / span > < / div >
< div class = "line" > < span class = "lineno" > 277< / span > < span class = "keyword" > const< / span > < span class = "keywordtype" > int< / span > N = 50; < span class = "comment" > // number of sample points< / span > < / div >
< div class = "line" > < span class = "lineno" > 278< / span > < / div >
< div class = "line" > < span class = "lineno" > 279< / span > < span class = "keywordtype" > double< / span > **X = (< span class = "keywordtype" > double< / span > **)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (N * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > double< / span > *));< / div >
< div class = "line" > < span class = "lineno" > 280< / span > < span class = "keywordtype" > int< / span > *Y = (< span class = "keywordtype" > int< / span > *)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (N * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > int< / span > )); < span class = "comment" > // corresponding y-values< / span > < / div >
< div class = "line" > < span class = "lineno" > 281< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++) X[i] = (< span class = "keywordtype" > double< / span > *)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (2 * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > double< / span > ));< / div >
< div class = "line" > < span class = "lineno" > 282< / span > < / div >
< div class = "line" > < span class = "lineno" > 283< / span > < span class = "comment" > // generate sample points in the interval< / span > < / div >
< div class = "line" > < span class = "lineno" > 284< / span > < span class = "comment" > // [-range2/100 , (range2-1)/100]< / span > < / div >
< div class = "line" > < span class = "lineno" > 285< / span > < span class = "keywordtype" > int< / span > < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > = 500; < span class = "comment" > // sample points full-range< / span > < / div >
< div class = "line" > < span class = "lineno" > 286< / span > < span class = "keywordtype" > int< / span > range2 = < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > > > 1; < span class = "comment" > // sample points half-range< / span > < / div >
< div class = "line" > < span class = "lineno" > 287< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++)< / div >
< div class = "line" > < span class = "lineno" > 288< / span > {< / div >
< div class = "line" > < span class = "lineno" > 289< / span > < span class = "keywordtype" > double< / span > x0 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 290< / span > < span class = "keywordtype" > double< / span > x1 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 291< / span > X[i][0] = x0;< / div >
< div class = "line" > < span class = "lineno" > 292< / span > X[i][1] = x1;< / div >
< div class = "line" > < span class = "lineno" > 293< / span > Y[i] = (x0 + 3. * x1) > -1 ? 1 : -1;< / div >
< div class = "line" > < span class = "lineno" > 294< / span > }< / div >
< div class = "line" > < span class = "lineno" > 295< / span > < / div >
< div class = "line" > < span class = "lineno" > 296< / span > printf(< span class = "stringliteral" > " ------- Test 2 -------\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 297< / span > printf(< span class = "stringliteral" > " Model before fit: %s\n" < / span > , < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (& ada));< / div >
< div class = "line" > < span class = "lineno" > 298< / span > < / div >
< div class = "line" > < span class = "lineno" > 299< / span > < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd" > adaline_fit< / a > (& ada, X, Y, N);< / div >
< div class = "line" > < span class = "lineno" > 300< / span > printf(< span class = "stringliteral" > " Model after fit: %s\n" < / span > , < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (& ada));< / div >
< div class = "line" > < span class = "lineno" > 301< / span > < / div >
< div class = "line" > < span class = "lineno" > 302< / span > < span class = "keywordtype" > int< / span > N_test_cases = 5;< / div >
< div class = "line" > < span class = "lineno" > 303< / span > < span class = "keywordtype" > double< / span > test_x[2];< / div >
< div class = "line" > < span class = "lineno" > 304< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N_test_cases; i++)< / div >
< div class = "line" > < span class = "lineno" > 305< / span > {< / div >
< div class = "line" > < span class = "lineno" > 306< / span > < span class = "keywordtype" > double< / span > x0 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 307< / span > < span class = "keywordtype" > double< / span > x1 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 308< / span > < / div >
< div class = "line" > < span class = "lineno" > 309< / span > test_x[0] = x0;< / div >
< div class = "line" > < span class = "lineno" > 310< / span > test_x[1] = x1;< / div >
< div class = "line" > < span class = "lineno" > 311< / span > < span class = "keywordtype" > int< / span > pred = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94" > adaline_predict< / a > (& ada, test_x, NULL);< / div >
< div class = "line" > < span class = "lineno" > 312< / span > printf(< span class = "stringliteral" > " Predict for x=(% 3.2f,% 3.2f): % d\n" < / span > , x0, x1, pred);< / div >
< div class = "line" > < span class = "lineno" > 313< / span > < / div >
< div class = "line" > < span class = "lineno" > 314< / span > < span class = "keywordtype" > int< / span > expected_val = (x0 + 3. * x1) > -1 ? 1 : -1;< / div >
< div class = "line" > < span class = "lineno" > 315< / span > assert(pred == expected_val);< / div >
< div class = "line" > < span class = "lineno" > 316< / span > printf(< span class = "stringliteral" > " ...passed\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 317< / span > }< / div >
< div class = "line" > < span class = "lineno" > 318< / span > < / div >
< div class = "line" > < span class = "lineno" > 319< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++) < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (X[i]);< / div >
< div class = "line" > < span class = "lineno" > 320< / span > < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (X);< / div >
< div class = "line" > < span class = "lineno" > 321< / span > < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (Y);< / div >
< div class = "line" > < span class = "lineno" > 322< / span > < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665" > delete_adaline< / a > (& ada);< / div >
< div class = "line" > < span class = "lineno" > 323< / span > }< / div >
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< div class = "ttc" id = "astructdata_html" > < div class = "ttname" > < a href = "../../df/dea/structdata.html" > data< / a > < / div > < div class = "ttdef" > < b > Definition:< / b > prime_factoriziation.c:25< / div > < / div >
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< / div > <!-- fragment --> < div class = "dynheader" >
Here is the call graph for this function:< / div >
< div class = "dyncontent" >
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< div class = "center" > < div class = "zoom" > < iframe scrolling = "no" frameborder = "0" src = "../../dd/d8c/adaline__learning_8c_a05cc9a0acb524fde727a4d7b4a747ee6_cgraph.svg" width = "100%" height = "478" > < p > < b > This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.< / b > < / p > < / iframe > < / div >
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< / div >
< / div >
< / div >
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< a id = "a3f37b9f073f7e57fd0b39d70718af1b1" name = "a3f37b9f073f7e57fd0b39d70718af1b1" > < / a >
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< h2 class = "memtitle" > < span class = "permalink" > < a href = "#a3f37b9f073f7e57fd0b39d70718af1b1" > ◆   < / a > < / span > test3()< / h2 >
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< div class = "memitem" >
< div class = "memproto" >
< table class = "memname" >
< tr >
< td class = "memname" > void test3 < / td >
< td > (< / td >
< td class = "paramtype" > double  < / td >
< td class = "paramname" > < em > eta< / em > < / td > < td > )< / td >
< td > < / td >
< / tr >
< / table >
< / div > < div class = "memdoc" >
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< p > test function to predict points in a 3D coordinate system lying within the sphere of radius 1 and centre at origin as +1 and others as -1. < / p >
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< p > Note that each point is defined by 3 values but we use 6 features. The function will create random sample points for training and test purposes. The sphere centred at origin and radius 1 is defined as: \(x^2+y^2+z^2=r^2=1\) and if the \(r^2< 1\), point lies within the sphere else, outside.< / p >
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< dl class = "params" > < dt > Parameters< / dt > < dd >
< table class = "params" >
< tr > < td class = "paramdir" > [in]< / td > < td class = "paramname" > eta< / td > < td > learning rate (optional, default=0.01) < / td > < / tr >
< / table >
< / dd >
< / dl >
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< div class = "fragment" > < div class = "line" > < span class = "lineno" > 337< / span > {< / div >
< div class = "line" > < span class = "lineno" > 338< / span > < span class = "keyword" > struct < / span > < a class = "code hl_struct" href = "../../d2/daa/structadaline.html" > adaline< / a > ada = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gacd88962c5f6341e43cbc69b4a7d3485b" > new_adaline< / a > (6, < a class = "code hl_variable" href = "../../d2/daa/structadaline.html#a85dbd7cce6195d11ebb388220b96bde2" > eta< / a > ); < span class = "comment" > // 2 features< / span > < / div >
< div class = "line" > < span class = "lineno" > 339< / span > < / div >
< div class = "line" > < span class = "lineno" > 340< / span > < span class = "keyword" > const< / span > < span class = "keywordtype" > int< / span > N = 50; < span class = "comment" > // number of sample points< / span > < / div >
< div class = "line" > < span class = "lineno" > 341< / span > < / div >
< div class = "line" > < span class = "lineno" > 342< / span > < span class = "keywordtype" > double< / span > **X = (< span class = "keywordtype" > double< / span > **)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (N * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > double< / span > *));< / div >
< div class = "line" > < span class = "lineno" > 343< / span > < span class = "keywordtype" > int< / span > *Y = (< span class = "keywordtype" > int< / span > *)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (N * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > int< / span > )); < span class = "comment" > // corresponding y-values< / span > < / div >
< div class = "line" > < span class = "lineno" > 344< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++) X[i] = (< span class = "keywordtype" > double< / span > *)< a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a725f50ecaf1959d96de79b36b4788fee" > malloc< / a > (6 * < span class = "keyword" > sizeof< / span > (< span class = "keywordtype" > double< / span > ));< / div >
< div class = "line" > < span class = "lineno" > 345< / span > < / div >
< div class = "line" > < span class = "lineno" > 346< / span > < span class = "comment" > // generate sample points in the interval< / span > < / div >
< div class = "line" > < span class = "lineno" > 347< / span > < span class = "comment" > // [-range2/100 , (range2-1)/100]< / span > < / div >
< div class = "line" > < span class = "lineno" > 348< / span > < span class = "keywordtype" > int< / span > < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > = 200; < span class = "comment" > // sample points full-range< / span > < / div >
< div class = "line" > < span class = "lineno" > 349< / span > < span class = "keywordtype" > int< / span > range2 = < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > > > 1; < span class = "comment" > // sample points half-range< / span > < / div >
< div class = "line" > < span class = "lineno" > 350< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++)< / div >
< div class = "line" > < span class = "lineno" > 351< / span > {< / div >
< div class = "line" > < span class = "lineno" > 352< / span > < span class = "keywordtype" > double< / span > x0 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 353< / span > < span class = "keywordtype" > double< / span > x1 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 354< / span > < span class = "keywordtype" > double< / span > x2 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 355< / span > X[i][0] = x0;< / div >
< div class = "line" > < span class = "lineno" > 356< / span > X[i][1] = x1;< / div >
< div class = "line" > < span class = "lineno" > 357< / span > X[i][2] = x2;< / div >
< div class = "line" > < span class = "lineno" > 358< / span > X[i][3] = x0 * x0;< / div >
< div class = "line" > < span class = "lineno" > 359< / span > X[i][4] = x1 * x1;< / div >
< div class = "line" > < span class = "lineno" > 360< / span > X[i][5] = x2 * x2;< / div >
< div class = "line" > < span class = "lineno" > 361< / span > Y[i] = (x0 * x0 + x1 * x1 + x2 * x2) < = 1 ? 1 : -1;< / div >
< div class = "line" > < span class = "lineno" > 362< / span > }< / div >
< div class = "line" > < span class = "lineno" > 363< / span > < / div >
< div class = "line" > < span class = "lineno" > 364< / span > printf(< span class = "stringliteral" > " ------- Test 3 -------\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 365< / span > printf(< span class = "stringliteral" > " Model before fit: %s\n" < / span > , < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (& ada));< / div >
< div class = "line" > < span class = "lineno" > 366< / span > < / div >
< div class = "line" > < span class = "lineno" > 367< / span > < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gaa52120912e32d2893fe1c6d78da5befd" > adaline_fit< / a > (& ada, X, Y, N);< / div >
< div class = "line" > < span class = "lineno" > 368< / span > printf(< span class = "stringliteral" > " Model after fit: %s\n" < / span > , < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gadb1a7acb555ad62daaf3806bf2fed036" > adaline_get_weights_str< / a > (& ada));< / div >
< div class = "line" > < span class = "lineno" > 369< / span > < / div >
< div class = "line" > < span class = "lineno" > 370< / span > < span class = "keywordtype" > int< / span > N_test_cases = 5;< / div >
< div class = "line" > < span class = "lineno" > 371< / span > < span class = "keywordtype" > double< / span > test_x[6];< / div >
< div class = "line" > < span class = "lineno" > 372< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N_test_cases; i++)< / div >
< div class = "line" > < span class = "lineno" > 373< / span > {< / div >
< div class = "line" > < span class = "lineno" > 374< / span > < span class = "keywordtype" > double< / span > x0 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 375< / span > < span class = "keywordtype" > double< / span > x1 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 376< / span > < span class = "keywordtype" > double< / span > x2 = ((rand() % < a class = "code hl_struct" href = "../../df/dea/structdata.html" > range< / a > ) - range2) / 100.f;< / div >
< div class = "line" > < span class = "lineno" > 377< / span > test_x[0] = x0;< / div >
< div class = "line" > < span class = "lineno" > 378< / span > test_x[1] = x1;< / div >
< div class = "line" > < span class = "lineno" > 379< / span > test_x[2] = x2;< / div >
< div class = "line" > < span class = "lineno" > 380< / span > test_x[3] = x0 * x0;< / div >
< div class = "line" > < span class = "lineno" > 381< / span > test_x[4] = x1 * x1;< / div >
< div class = "line" > < span class = "lineno" > 382< / span > test_x[5] = x2 * x2;< / div >
< div class = "line" > < span class = "lineno" > 383< / span > < span class = "keywordtype" > int< / span > pred = < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#gac70b578aee679005fd336073969c3d94" > adaline_predict< / a > (& ada, test_x, NULL);< / div >
< div class = "line" > < span class = "lineno" > 384< / span > printf(< span class = "stringliteral" > " Predict for x=(% 3.2f,% 3.2f): % d\n" < / span > , x0, x1, pred);< / div >
< div class = "line" > < span class = "lineno" > 385< / span > < / div >
< div class = "line" > < span class = "lineno" > 386< / span > < span class = "keywordtype" > int< / span > expected_val = (x0 * x0 + x1 * x1 + x2 * x2) < = 1 ? 1 : -1;< / div >
< div class = "line" > < span class = "lineno" > 387< / span > assert(pred == expected_val);< / div >
< div class = "line" > < span class = "lineno" > 388< / span > printf(< span class = "stringliteral" > " ...passed\n" < / span > );< / div >
< div class = "line" > < span class = "lineno" > 389< / span > }< / div >
< div class = "line" > < span class = "lineno" > 390< / span > < / div >
< div class = "line" > < span class = "lineno" > 391< / span > < span class = "keywordflow" > for< / span > (< span class = "keywordtype" > int< / span > i = 0; i < N; i++) < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (X[i]);< / div >
< div class = "line" > < span class = "lineno" > 392< / span > < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (X);< / div >
< div class = "line" > < span class = "lineno" > 393< / span > < a class = "code hl_define" href = "../../d2/ddd/malloc__dbg_8h.html#a9cc854374299a1dd933bf62029761768" > free< / a > (Y);< / div >
< div class = "line" > < span class = "lineno" > 394< / span > < a class = "code hl_function" href = "../../da/d2a/group__adaline.html#ga6f35caa3084772cc126ac7b20f67f665" > delete_adaline< / a > (& ada);< / div >
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< li class = "footer" > Generated by < a href = "https://www.doxygen.org/index.html" > < img class = "footer" src = "../../doxygen.svg" width = "104" height = "31" alt = "doxygen" / > < / a > 1.9.6 < / li >
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