//
// C++: static Ptr_DTrees cv::ml::DTrees::load(String filepath, String nodeName = String())
//
//javadoc: DTrees::load(filepath, nodeName)
public static DTrees load(string filepath, string nodeName)
{
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
DTrees retVal = DTrees.__fromPtr__(ml_DTrees_load_10(filepath, nodeName));
return(retVal);
#else
return(null);
#endif
}
//
// C++: static Ptr_DTrees cv::ml::DTrees::create()
//
//javadoc: DTrees::create()
public static DTrees create()
{
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
DTrees retVal = DTrees.__fromPtr__(ml_DTrees_create_10());
return(retVal);
#else
return(null);
#endif
}
/**
* Loads and creates a serialized DTrees from a file
*
* Use DTree::save to serialize and store an DTree to disk.
* Load the DTree from this file again, by calling this function with the path to the file.
* Optionally specify the node for the file containing the classifier
*
* param filepath path to serialized DTree
* return automatically generated
*/
public static DTrees load(string filepath)
{
return(DTrees.__fromPtr__(ml_DTrees_load_11(filepath)));
}
//
// C++: static Ptr_DTrees cv::ml::DTrees::create()
//
/**
* Creates the empty model
*
* The static method creates empty decision tree with the specified parameters. It should be then
* trained using train method (see StatModel::train). Alternatively, you can load the model from
* file using Algorithm::load<DTrees>(filename).
* return automatically generated
*/
public static DTrees create()
{
return(DTrees.__fromPtr__(ml_DTrees_create_10()));
}
//
// C++: static Ptr_DTrees cv::ml::DTrees::load(String filepath, String nodeName = String())
//
/**
* Loads and creates a serialized DTrees from a file
*
* Use DTree::save to serialize and store an DTree to disk.
* Load the DTree from this file again, by calling this function with the path to the file.
* Optionally specify the node for the file containing the classifier
*
* param filepath path to serialized DTree
* param nodeName name of node containing the classifier
* return automatically generated
*/
public static DTrees load(string filepath, string nodeName)
{
return(DTrees.__fromPtr__(ml_DTrees_load_10(filepath, nodeName)));
}