// // 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))); }