Hello!
My intention is to use a Random Forest Ensemble, trained previously in Matlab, in a Java application. My Matlab function, which I compiled, using deploytool is:
function [Probability]=PredictingTest (Predictor)
load (['D:/Test/Tree.mat'], 'Tree')
[~, prob]=predict(Tree , Predictor);
Probability=prob(:,1);
end
Where:
- Predictor input is an integer between -10 to 10.
- Probability output is a double between 0 to 1.
- Tree is a .mat file with a CompactTreeBagger object stored in it.
Next I deploy the jar files to my Eclipse project, and try to run this Java code:
/* Necessary package imports */
import com.mathworks.toolbox.javabuilder.*;
import PredictTest.*;
public class predict_test {
static MWNumericArray rhs = null; /* Stores input value */
static PredictTest prediction;
static Object[] result = null; /* Stores the result */
public static void main(String[] args) {
try {
prediction = new PredictTest();
rhs=new MWNumericArray(5,MWClassID.DOUBLE);
result=prediction.PredictingTest(1, rhs);
}
catch (MWException e) {
e.printStackTrace();
}}}
Sadly what I get is this exception:
{Warning: Variable 'Tree' originally saved as a CompactTreeBagger cannot be instantiated as an object and will be read in as a uint32.}
> In PredictingTest at 3
{??? Undefined function or method 'predict' for input arguments of type 'uint32'.
So, as far as I understood, this means that Java can't use Matlab objects even by the methods, compiled from Matlab functions. It will be very nice if I could get some help on how can I overcome this. It is very important to me. Thank you all in advance!
P.S I'm surely not confined to a Matlab TreeBagger algorithm. If there is a Java package you are familiar with, that can do the work, it can be a nice solution too.
