Plotting gradient descent graphically on Windows

My previous example showed how to plot gradient descent using GNUPlot on Linux, but there was no workaround for running it on Windows. Here I will show you how using Mingw and Javaplot.

First, install mingw here (Make sure to keep the default install settings and directory)

Then get JavaPlot here Extract it somewhere you know where it will be.

Next open up a project in eclipse. Right click on the project and click Build Path -> Add External Archives. Find JavaPlot.jar and add it and then right click on your project again and click refresh. You should now be able to use JavaPlot. The source below is the same as the previous tutorial except that it plots using GNUPlot. Note that theta1 is not used. Your left side of the screen should look like this:

import com.panayotis.gnuplot.JavaPlot;

public class GradDescent {

    public static void main(String[] args) {
   
       
       
         float x[] = {1f,2f,3f,4f,5f,6f,7f,8f,9f,10f};   
         float y[] = {2f,5f,10f,17f,26f,37f,50f,65f,82f,101f};   
       
         /*number of examples*/
         int m = 10;
       
          /*thetas and temp thetas*/
            float theta0, temp0, theta1, temp1, theta2, temp2;
            theta0 = 0.0f; temp0 = 0.0f;
            theta1 = 0.0f; temp1 = 0.0f;
            theta2 = 0.0f; temp2 = 0.0f;
         
        /*# of iterations and learning rate*/
            int iterations = 3430000;
            float alpha = 0.003f;

            int j = 0;
            float h0 = 0.0f;
            float h1 = 0.0f;
            float h2 = 0.0f;
            int i = 0;
            for(i = 0; i < iterations; i++)
            {
         
                h0 = 0.0f;
                h1 = 0.0f;
                h2 = 0.0f;
                for(j = 0; j<m; j++)
                {
                    h0 = h0 + ((theta0 +  x[j]*x[j]*theta2) - y[j]);
                    h1 = h1 + ((theta0 +  x[j]*x[j]*theta2) - y[j])*x[j];
                    h2 = h2 + ((theta0 +  x[j]*x[j]*theta2) - y[j])*x[j];
                }    
        temp0 = theta0 - (alpha*h0)/(float)m;
        temp1 = theta1 - (alpha*h1)/(float)m;
        temp2 = theta2 - (alpha*h2)/(float)m;
        theta0 = temp0;
        theta1 = temp1;
        theta2 = temp2;
        }
           
       System.out.println("" + theta2 + "x^2 + " + theta1 + "x + " + theta0);
      
       testGradientDescent(2f, theta0, theta1, theta2);

    }
   
    private static void testGradientDescent(float n, float theta0, float theta1, float theta2)
    {
        float result = theta0 + (theta1*n) + (theta2*n*n);
        //float x[] = {1f,2f,3f,4f,5f,6f,7f,8f,9f,10f};   
        //float y[] = {2f,5f,10f,17f,26f,37f,50f,65f,82f,101f};
        int marks[][]={{1,2},{2,5},{3,10},{4,17},{5,26},{6,37},{7,50},{8,65},{9,82},{10,101}};
       
        System.out.println("Result: " + result);
        String outputFunction = String.valueOf(String.valueOf(theta0)  + "+" + String.valueOf(theta2) + "*x*x");
        System.out.println("Plotting " + outputFunction);
        JavaPlot p = new JavaPlot();
        p.addPlot(marks);
       
        p.addPlot(outputFunction);
        p.setPersist(true);
        p.plot();
        p.setPersist(true);
       
    }

}

At the end, I needed to convert our data set into a multi dimensional matrix for JavaPlot to plot the points with the curve.