You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: classRF_train.m
    path of file: ./repos/Image-Harmonization-Dataset-iHarmony4/Xue et al/demo/rf_class_c
    
    the code of the file until where you have to start completion: %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls the mex file
% This does training 
    
function model = classRF_train(X,Y,ntree,mtry, extra_options)
% 
%___Options
% requires 2 arguments and the rest 3 are optional
% X: data matrix
% Y: target values 
% ntree (optional): number of trees (default is 500). also if set to 0
%           will default to 500
% mtry (default is floor(sqrt(size(X,2))) D=number of features in X). also if set to 0
%           will default to 500
%
%
% Note: TRUE = 1 and FALSE = 0 below
% extra_options represent a structure containing various misc. options to
%      control the RF
%  extra_options.replace = 0 or 1 (default is 1) sampling with or without
%                           replacement
%  extra_options.classwt = priors of classes. Here the function first gets
%                       the labels in ascend