updated prototype for logistic regression classifier

modules/ml/include/opencv2/ml.hpp

@@ -581,17 +581,17 @@ struct CV_EXPORTS LogisticRegressionParams
     int regularized;
     int train_method;
     int mini_batch_size;
-    CvTermCriteria term_crit;
+    cv::TermCriteria term_crit;
 
     LogisticRegressionParams();
-    LogisticRegressionParams(double alpha, int num_iters, int norm, int regularized, int train_method, int minbatchsize);
+    LogisticRegressionParams(double learning_rate, int iters, int train_method, int normlization, int reg, int mini_batch_size);
+    
 };
 
 class CV_EXPORTS LogisticRegression
 {
 public:
-
-    LogisticRegression();
+    LogisticRegression( const LogisticRegressionParams& params);
     LogisticRegression(cv::InputArray data_ip, cv::InputArray labels_ip, const LogisticRegressionParams& params);
     virtual ~LogisticRegression();
 
@@ -601,10 +601,11 @@ public:
     virtual bool train(cv::InputArray data_ip, cv::InputArray label_ip);
     virtual void predict( cv::InputArray data, cv::OutputArray predicted_labels ) const;
 
-    virtual void save(std::string filepath) const;
-    virtual void load(const std::string filepath);
+    virtual void write(FileStorage& fs) const;
+    virtual void read(const FileNode& fn);
 
-    cv::Mat get_learnt_thetas() const;
+    const cv::Mat get_learnt_thetas() const;
+    virtual void clear();
 
 protected:
 
@@ -623,11 +624,6 @@ protected:
     virtual cv::Mat compute_mini_batch_gradient(const cv::Mat& data, const cv::Mat& labels, const cv::Mat& init_theta);
     virtual bool set_label_map(const cv::Mat& labels);
     static cv::Mat remap_labels(const cv::Mat& labels, const std::map<int, int>& lmap);
-
-    virtual void write(FileStorage& fs) const;
-    virtual void read(const FileNode& fn);
-    virtual void clear();
-
 };
 }// namespace cv