diff --git a/modules/ml/include/opencv2/ml.hpp b/modules/ml/include/opencv2/ml.hpp
index 346df8f15..75fb6d134 100644
--- a/modules/ml/include/opencv2/ml.hpp
+++ b/modules/ml/include/opencv2/ml.hpp
@@ -1588,7 +1588,6 @@ public:
     ASGD is often the preferable choice. */
     enum SvmsgdType
     {
-        ILLEGAL_SVMSGD_TYPE,
         SGD, //!< Stochastic Gradient Descent
         ASGD //!< Average Stochastic Gradient Descent
     };
@@ -1596,7 +1595,6 @@ public:
     /** Margin type.*/
     enum MarginType
     {
-        ILLEGAL_MARGIN_TYPE,
         SOFT_MARGIN, //!< General case, suits to the case of non-linearly separable sets, allows outliers.
         HARD_MARGIN  //!< More accurate for the case of linearly separable sets.
     };
diff --git a/modules/ml/src/svmsgd.cpp b/modules/ml/src/svmsgd.cpp
index 77ac2ad67..0f1efcfea 100644
--- a/modules/ml/src/svmsgd.cpp
+++ b/modules/ml/src/svmsgd.cpp
@@ -89,14 +89,8 @@ public:
 
     virtual void setOptimalParameters(int svmsgdType = ASGD, int marginType = SOFT_MARGIN);
 
-    virtual int getSvmsgdType() const;
-
-    virtual void setSvmsgdType(int svmsgdType);
-
-    virtual int getMarginType() const;
-
-    virtual void setMarginType(int marginType);
-
+    CV_IMPL_PROPERTY(int, SvmsgdType, params.svmsgdType)
+    CV_IMPL_PROPERTY(int, MarginType, params.marginType)
     CV_IMPL_PROPERTY(float, Lambda, params.lambda)
     CV_IMPL_PROPERTY(float, Gamma0, params.gamma0)
     CV_IMPL_PROPERTY(float, C, params.c)
@@ -132,8 +126,8 @@ private:
         float gamma0;                             //learning rate
         float c;
         TermCriteria termCrit;
-        SvmsgdType svmsgdType;
-        MarginType marginType;
+        int svmsgdType;
+        int marginType;
     };
 
     SVMSGDParams params;
@@ -148,9 +142,9 @@ std::pair<bool,bool> SVMSGDImpl::areClassesEmpty(Mat responses)
 {
     CV_Assert(responses.cols == 1 || responses.rows == 1);
     std::pair<bool,bool> emptyInClasses(true, true);
-    int limit_index = responses.rows;
+    int limitIndex = responses.rows;
 
-    for(int index = 0; index < limit_index; index++)
+    for(int index = 0; index < limitIndex; index++)
     {
         if (isPositive(responses.at<float>(index)))
             emptyInClasses.first = false;
@@ -276,9 +270,9 @@ bool SVMSGDImpl::train(const Ptr<TrainData>& data, int)
     int extendedTrainSamplesCount = extendedTrainSamples.rows;
     int extendedFeatureCount = extendedTrainSamples.cols;
 
-    Mat extendedWeights = Mat::zeros(1, extendedFeatureCount, CV_32F);         // Initialize extendedWeights vector with zeros
-    Mat previousWeights = Mat::zeros(1, extendedFeatureCount, CV_32F);     //extendedWeights vector for calculating terminal criterion
-    Mat averageExtendedWeights;                                        //average extendedWeights vector for ASGD model
+    Mat extendedWeights = Mat::zeros(1, extendedFeatureCount, CV_32F);
+    Mat previousWeights = Mat::zeros(1, extendedFeatureCount, CV_32F);
+    Mat averageExtendedWeights;
     if (params.svmsgdType == ASGD)
     {
         averageExtendedWeights = Mat::zeros(1, extendedFeatureCount, CV_32F);
@@ -407,10 +401,8 @@ void SVMSGDImpl::writeParams( FileStorage& fs ) const
     case ASGD:
         SvmsgdTypeStr = "ASGD";
         break;
-    case ILLEGAL_SVMSGD_TYPE:
-        SvmsgdTypeStr = format("Unknown_%d", params.svmsgdType);
     default:
-        std::cout << "params.svmsgdType isn't initialized" << std::endl;
+        SvmsgdTypeStr = format("Unknown_%d", params.svmsgdType);
     }
 
     fs << "svmsgdType" << SvmsgdTypeStr;
@@ -425,10 +417,8 @@ void SVMSGDImpl::writeParams( FileStorage& fs ) const
     case HARD_MARGIN:
         marginTypeStr = "HARD_MARGIN";
         break;
-    case ILLEGAL_MARGIN_TYPE:
-        marginTypeStr = format("Unknown_%d", params.marginType);
     default:
-        std::cout << "params.marginType isn't initialized" << std::endl;
+        marginTypeStr = format("Unknown_%d", params.marginType);
     }
 
     fs << "marginType" << marginTypeStr;
@@ -458,21 +448,21 @@ void SVMSGDImpl::read(const FileNode& fn)
 void SVMSGDImpl::readParams( const FileNode& fn )
 {
     String svmsgdTypeStr = (String)fn["svmsgdType"];
-    SvmsgdType svmsgdType =
+    int svmsgdType =
             svmsgdTypeStr == "SGD" ? SGD :
-                                     svmsgdTypeStr == "ASGD" ? ASGD : ILLEGAL_SVMSGD_TYPE;
+                                     svmsgdTypeStr == "ASGD" ? ASGD : -1;
 
-    if( svmsgdType == ILLEGAL_SVMSGD_TYPE )
+    if( svmsgdType < 0 )
         CV_Error( CV_StsParseError, "Missing or invalid SVMSGD type" );
 
     params.svmsgdType = svmsgdType;
 
     String marginTypeStr = (String)fn["marginType"];
-    MarginType marginType =
+    int marginType =
             marginTypeStr == "SOFT_MARGIN" ? SOFT_MARGIN :
-                                     marginTypeStr == "HARD_MARGIN" ? HARD_MARGIN : ILLEGAL_MARGIN_TYPE;
+                                     marginTypeStr == "HARD_MARGIN" ? HARD_MARGIN : -1;
 
-    if( marginType == ILLEGAL_MARGIN_TYPE )
+    if( marginType < 0 )
         CV_Error( CV_StsParseError, "Missing or invalid margin type" );
 
     params.marginType = marginType;
@@ -510,8 +500,8 @@ SVMSGDImpl::SVMSGDImpl()
 {
     clear();
 
-    params.svmsgdType = ILLEGAL_SVMSGD_TYPE;
-    params.marginType = ILLEGAL_MARGIN_TYPE;
+    params.svmsgdType = -1;
+    params.marginType = -1;
 
     // Parameters for learning
     params.lambda = 0;                              // regularization
@@ -529,7 +519,7 @@ void SVMSGDImpl::setOptimalParameters(int svmsgdType, int marginType)
     case SGD:
         params.svmsgdType = SGD;
         params.marginType = (marginType == SOFT_MARGIN) ? SOFT_MARGIN :
-                            (marginType == HARD_MARGIN) ? HARD_MARGIN : ILLEGAL_MARGIN_TYPE;
+                            (marginType == HARD_MARGIN) ? HARD_MARGIN : -1;
         params.lambda = 0.0001f;
         params.gamma0 = 0.05f;
         params.c = 1.f;
@@ -539,7 +529,7 @@ void SVMSGDImpl::setOptimalParameters(int svmsgdType, int marginType)
     case ASGD:
         params.svmsgdType = ASGD;
         params.marginType = (marginType == SOFT_MARGIN) ? SOFT_MARGIN :
-                            (marginType == HARD_MARGIN) ? HARD_MARGIN : ILLEGAL_MARGIN_TYPE;
+                            (marginType == HARD_MARGIN) ? HARD_MARGIN : -1;
         params.lambda = 0.00001f;
         params.gamma0 = 0.05f;
         params.c = 0.75f;
@@ -550,45 +540,5 @@ void SVMSGDImpl::setOptimalParameters(int svmsgdType, int marginType)
         CV_Error( CV_StsParseError, "SVMSGD model data is invalid" );
     }
 }
-
-void SVMSGDImpl::setSvmsgdType(int type)
-{
-    switch (type)
-    {
-    case SGD:
-        params.svmsgdType = SGD;
-        break;
-    case ASGD:
-        params.svmsgdType = ASGD;
-        break;
-    default:
-        params.svmsgdType = ILLEGAL_SVMSGD_TYPE;
-    }
-}
-
-int SVMSGDImpl::getSvmsgdType() const
-{
-    return params.svmsgdType;
-}
-
-void SVMSGDImpl::setMarginType(int type)
-{
-    switch (type)
-    {
-    case HARD_MARGIN:
-        params.marginType = HARD_MARGIN;
-        break;
-    case SOFT_MARGIN:
-        params.marginType = SOFT_MARGIN;
-        break;
-    default:
-        params.marginType = ILLEGAL_MARGIN_TYPE;
-    }
-}
-
-int SVMSGDImpl::getMarginType() const
-{
-    return params.marginType;
-}
 }   //ml
 }   //cv