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268 lines
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<div class="headertitle"><div class="title">arm_bayes_example_f32.c</div></div>
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</div><!--header-->
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<div class="contents">
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<div class="fragment"><div class="line"><span class="comment">/* ----------------------------------------------------------------------</span></div>
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<div class="line"><span class="comment">* Copyright (C) 2019-2020 ARM Limited. All rights reserved.</span></div>
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<div class="line"><span class="comment">*</span></div>
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<div class="line"><span class="comment">* $Date: 09. December 2019</span></div>
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<div class="line"><span class="comment">* $Revision: V1.0.0</span></div>
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<div class="line"><span class="comment">*</span></div>
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<div class="line"><span class="comment">* Project: CMSIS DSP Library</span></div>
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<div class="line"><span class="comment">* Title: arm_bayes_example_f32.c</span></div>
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<div class="line"><span class="comment">*</span></div>
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<div class="line"><span class="comment">* Description: Example code demonstrating how to use Bayes functions.</span></div>
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<div class="line"><span class="comment">*</span></div>
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<div class="line"><span class="comment">* Target Processor: Cortex-M/Cortex-A</span></div>
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<div class="line"><span class="comment">*</span></div>
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<div class="line"><span class="comment">* Redistribution and use in source and binary forms, with or without</span></div>
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<div class="line"><span class="comment">* modification, are permitted provided that the following conditions</span></div>
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<div class="line"><span class="comment">* are met:</span></div>
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<div class="line"><span class="comment">* - Redistributions of source code must retain the above copyright</span></div>
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<div class="line"><span class="comment">* notice, this list of conditions and the following disclaimer.</span></div>
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<div class="line"><span class="comment">* - Redistributions in binary form must reproduce the above copyright</span></div>
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<div class="line"><span class="comment">* notice, this list of conditions and the following disclaimer in</span></div>
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<div class="line"><span class="comment">* the documentation and/or other materials provided with the</span></div>
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<div class="line"><span class="comment">* distribution.</span></div>
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<div class="line"><span class="comment">* - Neither the name of ARM LIMITED nor the names of its contributors</span></div>
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<div class="line"><span class="comment">* may be used to endorse or promote products derived from this</span></div>
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<div class="line"><span class="comment">* software without specific prior written permission.</span></div>
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<div class="line"><span class="comment">*</span></div>
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<div class="line"><span class="comment">* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS</span></div>
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<div class="line"><span class="comment">* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT</span></div>
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<div class="line"><span class="comment">* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS</span></div>
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<div class="line"><span class="comment">* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE</span></div>
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<div class="line"><span class="comment">* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,</span></div>
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<div class="line"><span class="comment">* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div>
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<div class="line"><span class="comment">* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;</span></div>
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<div class="line"><span class="comment">* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER</span></div>
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<div class="line"><span class="comment">* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT</span></div>
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<div class="line"><span class="comment">* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN</span></div>
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<div class="line"><span class="comment">* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE</span></div>
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<div class="line"><span class="comment">* POSSIBILITY OF SUCH DAMAGE.</span></div>
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<div class="line"><span class="comment">* -------------------------------------------------------------------- */</span></div>
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<div class="line"> </div>
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<div class="line"><span class="preprocessor">#include <math.h></span></div>
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<div class="line"><span class="preprocessor">#include <stdio.h></span></div>
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<div class="line"><span class="preprocessor">#include "<a class="code" href="arm__math_8h.html">arm_math.h</a>"</span></div>
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<div class="line"> </div>
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<div class="line"><span class="comment">/* </span></div>
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<div class="line"><span class="comment">Those parameters can be generated with the python library scikit-learn.</span></div>
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<div class="line"><span class="comment">*/</span></div>
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<div class="line"><a id="_a0" name="_a0"></a><a class="code hl_struct" href="structarm__gaussian__naive__bayes__instance__f32.html" title="Instance structure for Naive Gaussian Bayesian estimator.">arm_gaussian_naive_bayes_instance_f32</a> S;</div>
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<div class="line"> </div>
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<div class="line"><span class="preprocessor">#define NB_OF_CLASSES 3</span></div>
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<div class="line"><span class="preprocessor">#define VECTOR_DIMENSION 2</span></div>
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<div class="line"> </div>
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<div class="line"><span class="keyword">const</span> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> <a id="a1" name="a1"></a><a class="code hl_variable" href="arm__bayes__example__f32_8c.html#ae7fe0f955f8f87f9f8c171b7663542f2">theta</a>[<a id="a2" name="a2"></a><a class="code hl_define" href="arm__bayes__example__f32_8c.html#a29d34219689e613d2e2cf860c62b3061">NB_OF_CLASSES</a>*<a id="a3" name="a3"></a><a class="code hl_define" href="arm__bayes__example__f32_8c.html#a98d2e2076140b796ee1cb5f3e77248a7">VECTOR_DIMENSION</a>] = {</div>
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<div class="line"> 1.4539529436590528f, 0.8722776016801852f, </div>
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<div class="line"> -1.5267934452462473f, 0.903204577814203f, </div>
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<div class="line"> -0.15338006360932258f, -2.9997913665803964f</div>
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<div class="line">}; </div>
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<div class="line"><span class="keyword">const</span> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> <a id="a4" name="a4"></a><a class="code hl_variable" href="arm__bayes__example__f32_8c.html#ae008289e1f4de0874d81e2fc12933f3b">sigma</a>[<a class="code hl_define" href="arm__bayes__example__f32_8c.html#a29d34219689e613d2e2cf860c62b3061">NB_OF_CLASSES</a>*<a class="code hl_define" href="arm__bayes__example__f32_8c.html#a98d2e2076140b796ee1cb5f3e77248a7">VECTOR_DIMENSION</a>] = {</div>
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<div class="line"> 1.0063470889514925f, 0.9038018246524426f, </div>
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<div class="line"> 1.0224479953244736f, 0.7768764290432544f, </div>
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<div class="line"> 1.1217662403241206f, 1.2303890106020325f</div>
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<div class="line">}; </div>
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<div class="line"><span class="keyword">const</span> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> <a id="a5" name="a5"></a><a class="code hl_variable" href="arm__bayes__example__f32_8c.html#ac2318692fe990ccc10f1365545d93402">classPriors</a>[<a class="code hl_define" href="arm__bayes__example__f32_8c.html#a29d34219689e613d2e2cf860c62b3061">NB_OF_CLASSES</a>] = {</div>
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<div class="line"> 0.3333333333333333f, 0.3333333333333333f, 0.3333333333333333f</div>
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<div class="line">}; </div>
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<div class="line">int32_t <a id="a6" name="a6"></a><a class="code hl_function" href="arm__bayes__example__f32_8c.html#a52d2cba30e6946c95578be946ac12a65">main</a>(<span class="keywordtype">void</span>)</div>
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<div class="line">{</div>
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<div class="line"> <span class="comment">/* Array of input data */</span></div>
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<div class="line"> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> in[2];</div>
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<div class="line"> </div>
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<div class="line"> <span class="comment">/* Result of the classifier */</span></div>
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<div class="line"> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> result[<a class="code hl_define" href="arm__bayes__example__f32_8c.html#a29d34219689e613d2e2cf860c62b3061">NB_OF_CLASSES</a>];</div>
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|
<div class="line"> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> temp[<a class="code hl_define" href="arm__bayes__example__f32_8c.html#a29d34219689e613d2e2cf860c62b3061">NB_OF_CLASSES</a>];</div>
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<div class="line"> <a class="code hl_typedef" href="arm__math__types_8h.html#a4611b605e45ab401f02cab15c5e38715" title="32-bit floating-point type definition.">float32_t</a> maxProba;</div>
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<div class="line"> uint32_t index;</div>
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<div class="line"> </div>
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<div class="line"> S.<a id="a7" name="a7"></a><a class="code hl_variable" href="structarm__gaussian__naive__bayes__instance__f32.html#ac0020a4e04df9d200969b1ba84799d88">vectorDimension</a> = <a class="code hl_define" href="arm__bayes__example__f32_8c.html#a98d2e2076140b796ee1cb5f3e77248a7">VECTOR_DIMENSION</a>; </div>
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<div class="line"> S.<a id="a8" name="a8"></a><a class="code hl_variable" href="structarm__gaussian__naive__bayes__instance__f32.html#a40aa206e9576a40e06c7eafbf881b49e">numberOfClasses</a> = <a class="code hl_define" href="arm__bayes__example__f32_8c.html#a29d34219689e613d2e2cf860c62b3061">NB_OF_CLASSES</a>; </div>
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<div class="line"> S.<a id="a9" name="a9"></a><a class="code hl_variable" href="structarm__gaussian__naive__bayes__instance__f32.html#a60ddd36c1b1e0c25bc9d3e09e59c7d40">theta</a> = <a class="code hl_variable" href="arm__bayes__example__f32_8c.html#ae7fe0f955f8f87f9f8c171b7663542f2">theta</a>; </div>
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<div class="line"> S.<a id="a10" name="a10"></a><a class="code hl_variable" href="structarm__gaussian__naive__bayes__instance__f32.html#a42033b12e3779c533791e69d144bf8b0">sigma</a> = <a class="code hl_variable" href="arm__bayes__example__f32_8c.html#ae008289e1f4de0874d81e2fc12933f3b">sigma</a>; </div>
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<div class="line"> S.<a id="a11" name="a11"></a><a class="code hl_variable" href="structarm__gaussian__naive__bayes__instance__f32.html#a3643f22834fcd6a940367776b7ef3674">classPriors</a> = <a class="code hl_variable" href="arm__bayes__example__f32_8c.html#ac2318692fe990ccc10f1365545d93402">classPriors</a>; </div>
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<div class="line"> S.<a id="a12" name="a12"></a><a class="code hl_variable" href="structarm__gaussian__naive__bayes__instance__f32.html#ad2b99521268e7cfcceceb2a14dd8b9a1">epsilon</a>=4.328939296523643e-09f; </div>
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<div class="line"> </div>
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<div class="line"> in[0] = 1.5f;</div>
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<div class="line"> in[1] = 1.0f;</div>
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<div class="line"> </div>
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<div class="line"> index = <a id="a13" name="a13"></a><a class="code hl_function" href="group__groupBayes.html#ga23f942747fc13865a66bf14bb44dd299" title="Naive Gaussian Bayesian Estimator.">arm_gaussian_naive_bayes_predict_f32</a>(&S, in, result,temp);</div>
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<div class="line"> </div>
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<div class="line"> maxProba = result[index];</div>
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<div class="line"> </div>
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<div class="line"><span class="preprocessor">#if defined(SEMIHOSTING)</span></div>
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<div class="line"> printf(<span class="stringliteral">"Class = %d\n"</span>, index);</div>
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<div class="line"> printf(<span class="stringliteral">"Max proba = %f\n"</span>, (<span class="keywordtype">double</span>)maxProba);</div>
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<div class="line"><span class="preprocessor">#endif</span></div>
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<div class="line"> </div>
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<div class="line"> in[0] = -1.5f;</div>
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<div class="line"> in[1] = 1.0f;</div>
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<div class="line"> </div>
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<div class="line"> index = <a class="code hl_function" href="group__groupBayes.html#ga23f942747fc13865a66bf14bb44dd299" title="Naive Gaussian Bayesian Estimator.">arm_gaussian_naive_bayes_predict_f32</a>(&S, in, result,temp);</div>
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|
<div class="line"> </div>
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<div class="line"> maxProba = result[index];</div>
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<div class="line"> </div>
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|
<div class="line"><span class="preprocessor">#if defined(SEMIHOSTING)</span></div>
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<div class="line"> printf(<span class="stringliteral">"Class = %d\n"</span>, index);</div>
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|
<div class="line"> printf(<span class="stringliteral">"Max proba = %f\n"</span>, (<span class="keywordtype">double</span>)maxProba);</div>
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<div class="line"><span class="preprocessor">#endif</span></div>
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<div class="line"> </div>
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<div class="line"> in[0] = 0.0f;</div>
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<div class="line"> in[1] = -3.0f;</div>
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<div class="line"> </div>
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<div class="line"> index = <a class="code hl_function" href="group__groupBayes.html#ga23f942747fc13865a66bf14bb44dd299" title="Naive Gaussian Bayesian Estimator.">arm_gaussian_naive_bayes_predict_f32</a>(&S, in, result,temp);</div>
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<div class="line"> </div>
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<div class="line"> maxProba = result[index];</div>
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<div class="line"> </div>
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<div class="line"><span class="preprocessor">#if defined(SEMIHOSTING)</span></div>
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<div class="line"> printf(<span class="stringliteral">"Class = %d\n"</span>, index);</div>
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<div class="line"> printf(<span class="stringliteral">"Max proba = %f\n"</span>, (<span class="keywordtype">double</span>)maxProba);</div>
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<div class="line"><span class="preprocessor">#endif</span></div>
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<div class="line"> </div>
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<div class="line"><span class="preprocessor">#if !defined(SEMIHOSTING)</span></div>
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<div class="line"> <span class="keywordflow">while</span> (1); <span class="comment">/* main function does not return */</span></div>
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<div class="line"><span class="preprocessor">#endif</span></div>
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<div class="line">}</div>
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<div class="line"> </div>
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<div class="line"> </div>
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<div class="line"> </div>
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</div><!-- fragment --> </div><!-- contents -->
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</div><!-- doc-content -->
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<!-- start footer part -->
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<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
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<ul>
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<li class="footer">
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<script type="text/javascript">
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<!--
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writeFooter.call(this);
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//-->
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</script>
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</li>
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</ul>
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</div>
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</body>
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</html>
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