1 /****************************************************************************** 2 * @file bayes_functions.h 3 * @brief Public header file for CMSIS DSP Library 4 * @version V1.10.0 5 * @date 08 July 2021 6 * Target Processor: Cortex-M and Cortex-A cores 7 ******************************************************************************/ 8 /* 9 * Copyright (c) 2010-2020 Arm Limited or its affiliates. All rights reserved. 10 * 11 * SPDX-License-Identifier: Apache-2.0 12 * 13 * Licensed under the Apache License, Version 2.0 (the License); you may 14 * not use this file except in compliance with the License. 15 * You may obtain a copy of the License at 16 * 17 * www.apache.org/licenses/LICENSE-2.0 18 * 19 * Unless required by applicable law or agreed to in writing, software 20 * distributed under the License is distributed on an AS IS BASIS, WITHOUT 21 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 22 * See the License for the specific language governing permissions and 23 * limitations under the License. 24 */ 25 26 27 #ifndef _BAYES_FUNCTIONS_H_ 28 #define _BAYES_FUNCTIONS_H_ 29 30 #include "arm_math_types.h" 31 #include "arm_math_memory.h" 32 33 #include "dsp/none.h" 34 #include "dsp/utils.h" 35 36 #include "dsp/statistics_functions.h" 37 38 /** 39 * @defgroup groupBayes Bayesian estimators 40 * 41 * Implement the naive gaussian Bayes estimator. 42 * The training must be done from scikit-learn. 43 * 44 * The parameters can be easily 45 * generated from the scikit-learn object. Some examples are given in 46 * DSP/Testing/PatternGeneration/Bayes.py 47 */ 48 49 #ifdef __cplusplus 50 extern "C" 51 { 52 #endif 53 54 /** 55 * @brief Instance structure for Naive Gaussian Bayesian estimator. 56 */ 57 typedef struct 58 { 59 uint32_t vectorDimension; /**< Dimension of vector space */ 60 uint32_t numberOfClasses; /**< Number of different classes */ 61 const float32_t *theta; /**< Mean values for the Gaussians */ 62 const float32_t *sigma; /**< Variances for the Gaussians */ 63 const float32_t *classPriors; /**< Class prior probabilities */ 64 float32_t epsilon; /**< Additive value to variances */ 65 } arm_gaussian_naive_bayes_instance_f32; 66 67 /** 68 * @brief Naive Gaussian Bayesian Estimator 69 * 70 * @param[in] S points to a naive bayes instance structure 71 * @param[in] in points to the elements of the input vector. 72 * @param[out] *pOutputProbabilities points to a buffer of length numberOfClasses containing estimated probabilities 73 * @param[out] *pBufferB points to a temporary buffer of length numberOfClasses 74 * @return The predicted class 75 * 76 */ 77 78 79 uint32_t arm_gaussian_naive_bayes_predict_f32(const arm_gaussian_naive_bayes_instance_f32 *S, 80 const float32_t * in, 81 float32_t *pOutputProbabilities, 82 float32_t *pBufferB); 83 84 85 #ifdef __cplusplus 86 } 87 #endif 88 89 #endif /* ifndef _BAYES_FUNCTIONS_H_ */ 90
