From fcfeb2451b32b7ea65e55104297529fb83cfed10 Mon Sep 17 00:00:00 2001
From: Rahul Kavi <rahulkavi@live.com>
Date: Mon, 5 Aug 2013 09:42:07 -0400
Subject: [PATCH] added logistic regression prototype

---
 modules/ml/include/opencv2/ml.hpp | 84 +++++++++++++++++++++++++++++++
 1 file changed, 84 insertions(+)

diff --git a/modules/ml/include/opencv2/ml.hpp b/modules/ml/include/opencv2/ml.hpp
index a5ce3010bf..ea90538a92 100644
--- a/modules/ml/include/opencv2/ml.hpp
+++ b/modules/ml/include/opencv2/ml.hpp
@@ -89,6 +89,8 @@ public:
     CV_PROP_RW double maxVal;
     CV_PROP_RW double logStep;
 };
+#define CV_TYPE_NAME_ML_LR          "opencv-ml-lr"
+
 
 
 class CV_EXPORTS TrainData
@@ -566,6 +568,85 @@ public:
     static Ptr<ANN_MLP> create(const Params& params=Params());
 };
 
+/****************************************************************************************\
+*                           Logistic Regression                                          *
+\****************************************************************************************/
+
+struct CV_EXPORTS_W_MAP CvLR_TrainParams
+{
+    CV_PROP_RW double alpha;
+    CV_PROP_RW int num_iters;
+    CV_PROP_RW int norm;
+    ///////////////////////////////////////////////////
+    // CV_PROP_RW int debug;
+    ///////////////////////////////////////////////////
+    CV_PROP_RW int regularized;
+    CV_PROP_RW int train_method;
+    CV_PROP_RW int minibatchsize;
+
+    CV_PROP_RW CvTermCriteria term_crit;
+
+    CvLR_TrainParams();
+    ///////////////////////////////////////////////////
+    // CvLR_TrainParams(double alpha, int num_iters, int norm, int debug, int regularized, int train_method, int minbatchsize);
+    ///////////////////////////////////////////////////
+    CvLR_TrainParams(double alpha, int num_iters, int norm, int regularized, int train_method, int minbatchsize);
+    ~CvLR_TrainParams();
+};
+
+class CV_EXPORTS_W CvLR : public CvStatModel
+{
+public:
+    CvLR();
+    // CvLR(const CvLR_TrainParams& Params);
+
+    CvLR(const cv::Mat& data, const cv::Mat& labels, const CvLR_TrainParams& params);
+
+    virtual ~CvLR();
+
+    enum { REG_L1=0, REG_L2 = 1};
+    enum { BATCH, MINI_BATCH};
+
+
+    virtual bool train(const cv::Mat& data, const cv::Mat& labels);//, const CvLR_TrainParams& params);
+
+    virtual float predict(const cv::Mat& data, cv::Mat& predicted_labels);
+    virtual float predict(const cv::Mat& data);
+
+    virtual void write( CvFileStorage* storage, const char* name ) const;
+    virtual void read( CvFileStorage* storage, CvFileNode* node );
+
+    virtual void clear();
+
+    virtual cv::Mat get_learnt_mat();
+
+protected:
+
+    cv::Mat learnt_thetas;
+    CvLR_TrainParams params;
+
+    std::map<int, int> forward_mapper;
+    std::map<int, int> reverse_mapper;
+
+    virtual bool set_default_params();
+    virtual cv::Mat calc_sigmoid(const cv::Mat& data);
+
+    virtual double compute_cost(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
+    virtual cv::Mat compute_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
+    virtual cv::Mat compute_mini_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
+
+    virtual std::map<int, int> get_label_map(const cv::Mat& labels);
+
+    virtual bool set_label_map(const cv::Mat& labels);
+    virtual cv::Mat remap_labels(const cv::Mat& labels, const std::map<int, int> lmap);
+
+    //cv::Mat Mapper;
+
+    cv::Mat labels_o;
+    cv::Mat labels_n;
+
+};
+
 /****************************************************************************************\
 *                           Auxilary functions declarations                              *
 \****************************************************************************************/
@@ -581,6 +662,9 @@ CV_EXPORTS void randGaussMixture( InputArray means, InputArray covs, InputArray
 /* creates test set */
 CV_EXPORTS void createConcentricSpheresTestSet( int nsamples, int nfeatures, int nclasses,
                                                 OutputArray samples, OutputArray responses);
+typedef CvLR_TrainParams LogisticRegression_TrainParams;
+typedef CvLR LogisticRegression;
+
 
 }
 }