📄 quadraticproblem.java
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/*
* YALE - Yet Another Learning Environment
* Copyright (C) 2001-2004
* Simon Fischer, Ralf Klinkenberg, Ingo Mierswa,
* Katharina Morik, Oliver Ritthoff
* Artificial Intelligence Unit
* Computer Science Department
* University of Dortmund
* 44221 Dortmund, Germany
* email: yale-team@lists.sourceforge.net
* web: http://yale.cs.uni-dortmund.de/
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License as
* published by the Free Software Foundation; either version 2 of the
* License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
* USA.
*/
package edu.udo.cs.mySVM.Optimizer;
public abstract class quadraticProblem
{
/*
*
* A quadratic optimization problem
*
*/
// Public variables that describe the quadratic problem
protected int n; // number of variables
static int m=1; // number of linear constraints, 1 for now
public double[] c;
public double[] H; // c' * x + 1/2 x' * H * x -> min
public double[] A;
public double[] b; // A * x = b
public double[] l;
public double[] u; // l <= x <= u
public double[] x;
public double max_allowed_error;
public quadraticProblem(){
n = 0;
lambda_eq=0.0d;
};
public void set_n(int new_n){
n = new_n;
c = new double[n];
H = new double[n*n];
A = new double[n];
b = new double[n];
l = new double[n];
u = new double[n];
x = new double[n];
};
public int get_n(){
return(n);
};
public double lambda_eq;
protected abstract void calc_lambda_eq();
public abstract int solve();
};
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