digorithm

package GraphModels;

/**
 *
 * @author rodrigo
 */

public class Vertex {
    /* This Data Structure will be capable to represent a Vertex,

digorithm

/*
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* To change this template file, choose Tools | Templates
* and open the template in the editor.
*/

package GraphModels;

/**
 *

digorithm

/*
 * To change this license header, choose License Headers in Project Properties.
 * To change this template file, choose Tools | Templates
 * and open the template in the editor.
 */

package GraphModels;

import java.io.BufferedReader;
import java.io.FileNotFoundException;

digorithm

/*
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 * To change this template file, choose Tools | Templates
 * and open the template in the editor.
 */

package graphproject;
import GraphModels.*;
import java.io.IOException;
import java.util.ArrayList;

digorithm

import javax.swing.JFrame;
import org.math.plot.*;

public class InitialData{
	public static double[] x = {2, 4, 6, 8};
	public static double[] y = {2, 5, 5, 8};


	public void plotData(){
		Plot2DPanel plot = new Plot2DPanel();

digorithm

import javax.swing.JFrame;
import org.math.plot.*;

public class GradientDescent{
	private double theta0;
	private double theta1;

	private int trendline;

	// Algorithm settings

digorithm

public double hypothesisFunction(double x){
    	return this.theta1*x + theta0;
    }

digorithm

public double deriveTheta1(){
    	double sum = 0;

    	for (int j=0; j<initial_data.x.length; j++){
    		sum += (initial_data.y[j] - hypothesisFunction(initial_data.x[j])) * initial_data.x[j];
    	}
    	return -2 * sum / initial_data.x.length;
    }

    public double deriveTheta0(){

digorithm

public void execute(){
    	do {

    		this.theta1 -= alpha * deriveTheta1();
    		this.theta0 -= alpha * deriveTheta0();

    		//used for plotting
    		tplot[iters] = iters;
    		theta0plot[iters] = theta0;
    		theta1plot[iters] = theta1;

digorithm

public void addTrendLine(Plot2DPanel plot, boolean removePrev){
    	if (removePrev){
    		plot.removePlot(trendline);
    	}
    	double[] yEnd = new double[initial_data.x.length];
    	for (int i=0; i<initial_data.x.length; i++)
    		yEnd[i] = hypothesisFunction(initial_data.x[i]);
    	trendline = plot.addLinePlot("final", initial_data.x, yEnd);
    }