我正在测试 RISO 的 L-BFGS 库的实现,以实现 Java 中逻辑回归的函数最小化。这是我正在使用的课程的链接。
为了测试这个库,我试图最小化这个函数:
f(x) = 2*(x1^2) + 4*x2 + 5
该库需要我实现的目标和梯度函数,如下所示:
/**
The value of the objective function, given variable assignments
x. This is specific to your problem, so you must override it.
Remember that LBFGS only minimizes, so lower is better.
**/
public double objectiveFunction(double[] x) throws Exception {
return (2*x[0]*x[0] + 3*x[1] + 1);
}
/**
The gradient of the objective function, given variable assignments
x. This is specific to your problem, so you must override it.
**/
public double[] evaluateGradient(double[] x) throws Exception {
double[] result = new double[x.length];
result[0] = 4 * x[0];
result[1] = 3;
return result;
}
使用目标函数和梯度的这种实现运行代码会给我以下异常:
Exception in thread "main" Line search failed. See documentation of routine mcsrch.
Error return of line search: info = 3 Possible causes:
function or gradient are incorrect, or incorrect tolerances. (iflag == -1)
我没有更改默认值的公差。我究竟做错了什么?