?? svm.cs
字號:
alpha = new double[alpha_.Length];
alpha_.CopyTo(alpha, 0);
this.Cp = Cp;
this.Cn = Cn;
this.eps = eps;
this.unshrinked = false;
// initialize alpha_status
{
alpha_status = new sbyte[l];
for (int i = 0; i < l; i++)
update_alpha_status(i);
}
// initialize active set (for shrinking)
{
active_set = new int[l];
for (int i = 0; i < l; i++)
active_set[i] = i;
active_size = l;
}
// initialize gradient
{
G = new double[l];
G_bar = new double[l];
int i;
for (i = 0; i < l; i++)
{
G[i] = b[i];
G_bar[i] = 0;
}
for (i = 0; i < l; i++)
if (!is_lower_bound(i))
{
float[] Q_i = Q.get_Q(i, l);
double alpha_i = alpha[i];
int j;
for (j = 0; j < l; j++)
G[j] += alpha_i * Q_i[j];
if (is_upper_bound(i))
for (j = 0; j < l; j++)
G_bar[j] += get_C(i) * Q_i[j];
}
}
// optimization step
int iter = 0;
int counter = System.Math.Min(l, 1000) + 1;
int[] working_set = new int[2];
while (true)
{
// show progress and do shrinking
if (--counter == 0)
{
counter = System.Math.Min(l, 1000);
if (shrinking != 0)
do_shrinking();
System.Console.Error.Write(".");
}
if (select_working_set(working_set) != 0)
{
// reconstruct the whole gradient
reconstruct_gradient();
// reset active set size and check
active_size = l;
System.Console.Error.Write("*");
if (select_working_set(working_set) != 0)
break;
else
counter = 1; // do shrinking next iteration
}
int i = working_set[0];
int j = working_set[1];
++iter;
// update alpha[i] and alpha[j], handle bounds carefully
float[] Q_i = Q.get_Q(i, active_size);
float[] Q_j = Q.get_Q(j, active_size);
double C_i = get_C(i);
double C_j = get_C(j);
double old_alpha_i = alpha[i];
double old_alpha_j = alpha[j];
if (y[i] != y[j])
{
double delta = (- G[i] - G[j]) / System.Math.Max(Q_i[i] + Q_j[j] + 2 * Q_i[j], (float) 0);
double diff = alpha[i] - alpha[j];
alpha[i] += delta;
alpha[j] += delta;
if (diff > 0)
{
if (alpha[j] < 0)
{
alpha[j] = 0;
alpha[i] = diff;
}
}
else
{
if (alpha[i] < 0)
{
alpha[i] = 0;
alpha[j] = - diff;
}
}
if (diff > C_i - C_j)
{
if (alpha[i] > C_i)
{
alpha[i] = C_i;
alpha[j] = C_i - diff;
}
}
else
{
if (alpha[j] > C_j)
{
alpha[j] = C_j;
alpha[i] = C_j + diff;
}
}
}
else
{
double delta = (G[i] - G[j]) / System.Math.Max(Q_i[i] + Q_j[j] - 2 * Q_i[j], (float) 0);
double sum = alpha[i] + alpha[j];
alpha[i] -= delta;
alpha[j] += delta;
if (sum > C_i)
{
if (alpha[i] > C_i)
{
alpha[i] = C_i;
alpha[j] = sum - C_i;
}
}
else
{
if (alpha[j] < 0)
{
alpha[j] = 0;
alpha[i] = sum;
}
}
if (sum > C_j)
{
if (alpha[j] > C_j)
{
alpha[j] = C_j;
alpha[i] = sum - C_j;
}
}
else
{
if (alpha[i] < 0)
{
alpha[i] = 0;
alpha[j] = sum;
}
}
}
// update G
double delta_alpha_i = alpha[i] - old_alpha_i;
double delta_alpha_j = alpha[j] - old_alpha_j;
for (int k = 0; k < active_size; k++)
{
G[k] += Q_i[k] * delta_alpha_i + Q_j[k] * delta_alpha_j;
}
// update alpha_status and G_bar
{
bool ui = is_upper_bound(i);
bool uj = is_upper_bound(j);
update_alpha_status(i);
update_alpha_status(j);
int k;
if (ui != is_upper_bound(i))
{
Q_i = Q.get_Q(i, l);
if (ui)
for (k = 0; k < l; k++)
G_bar[k] -= C_i * Q_i[k];
else
for (k = 0; k < l; k++)
G_bar[k] += C_i * Q_i[k];
}
if (uj != is_upper_bound(j))
{
Q_j = Q.get_Q(j, l);
if (uj)
for (k = 0; k < l; k++)
G_bar[k] -= C_j * Q_j[k];
else
for (k = 0; k < l; k++)
G_bar[k] += C_j * Q_j[k];
}
}
}
// calculate rho
si.rho = calculate_rho();
// calculate objective value
{
double v = 0;
int i;
for (i = 0; i < l; i++)
v += alpha[i] * (G[i] + b[i]);
si.obj = v / 2;
}
// put back the solution
{
for (int i = 0; i < l; i++)
alpha_[active_set[i]] = alpha[i];
}
si.upper_bound_p = Cp;
si.upper_bound_n = Cn;
System.Console.Out.Write("\noptimization finished, #iter = " + iter + "\n");
}
// return 1 if already optimal, return 0 otherwise
internal virtual int select_working_set(int[] working_set)
{
// return i,j which maximize -grad(f)^T d , under constraint
// if alpha_i == C, d != +1
// if alpha_i == 0, d != -1
double Gmax1 = - INF; // max { -grad(f)_i * d | y_i*d = +1 }
int Gmax1_idx = - 1;
double Gmax2 = - INF; // max { -grad(f)_i * d | y_i*d = -1 }
int Gmax2_idx = - 1;
for (int i = 0; i < active_size; i++)
{
if (y[i] == + 1)
// y = +1
{
if (!is_upper_bound(i))
// d = +1
{
if (- G[i] > Gmax1)
{
Gmax1 = - G[i];
Gmax1_idx = i;
}
}
if (!is_lower_bound(i))
// d = -1
{
if (G[i] > Gmax2)
{
Gmax2 = G[i];
Gmax2_idx = i;
}
}
}
// y = -1
else
{
if (!is_upper_bound(i))
// d = +1
{
if (- G[i] > Gmax2)
{
Gmax2 = - G[i];
Gmax2_idx = i;
}
}
if (!is_lower_bound(i))
// d = -1
{
if (G[i] > Gmax1)
{
Gmax1 = G[i];
Gmax1_idx = i;
}
}
}
}
if (Gmax1 + Gmax2 < eps)
return 1;
working_set[0] = Gmax1_idx;
working_set[1] = Gmax2_idx;
return 0;
}
internal virtual void do_shrinking()
{
int i, j, k;
int[] working_set = new int[2];
if (select_working_set(working_set) != 0)
return ;
i = working_set[0];
j = working_set[1];
double Gm1 = (- y[j]) * G[j];
double Gm2 = y[i] * G[i];
// shrink
for (k = 0; k < active_size; k++)
{
if (is_lower_bound(k))
{
if (y[k] == + 1)
{
if (- G[k] >= Gm1)
continue;
}
else if (- G[k] >= Gm2)
continue;
}
else if (is_upper_bound(k))
{
if (y[k] == + 1)
{
if (G[k] >= Gm2)
continue;
}
else if (G[k] >= Gm1)
continue;
}
else
continue;
--active_size;
swap_index(k, active_size);
--k; // look at the newcomer
}
// unshrink, check all variables again before final iterations
if (unshrinked || - (Gm1 + Gm2) > eps * 10)
return ;
unshrinked = true;
reconstruct_gradient();
for (k = l - 1; k >= active_size; k--)
{
if (is_lower_bound(k))
{
if (y[k] == + 1)
{
if (- G[k] < Gm1)
continue;
}
else if (- G[k] < Gm2)
continue;
}
else if (is_upper_bound(k))
{
if (y[k] == + 1)
{
if (G[k] < Gm2)
continue;
}
else if (G[k] < Gm1)
continue;
}
else
continue;
swap_index(k, active_size);
active_size++;
++k; // look at the newcomer
}
}
internal virtual double calculate_rho()
{
double r;
int nr_free = 0;
double ub = INF, lb = - INF, sum_free = 0;
for (int i = 0; i < active_size; i++)
{
double yG = y[i] * G[i];
if (is_lower_bound(i))
{
if (y[i] > 0)
ub = System.Math.Min(ub, yG);
else
lb = System.Math.Max(lb, yG);
}
else if (is_upper_bound(i))
{
if (y[i] < 0)
ub = System.Math.Min(ub, yG);
else
lb = System.Math.Max(lb, yG);
}
else
{
++nr_free;
sum_free += yG;
}
}
if (nr_free > 0)
r = sum_free / nr_free;
else
r = (ub + lb) / 2;
return r;
}
}
//
// Solver for nu-svm classification and regression
//
// additional constraint: e^T \alpha = constant
//
sealed class Solver_NU:Solver
{
private SolutionInfo si;
internal override void Solve(int l, Kernel Q, double[] b, sbyte[] y, double[] alpha, double Cp, double Cn, double eps, SolutionInfo si, int shrinking)
{
this.si = si;
base.Solve(l, Q, b, y, alpha, Cp, Cn, eps, si, shrinking);
}
internal override int select_working_set(int[] working_set)
{
// return i,j which maximize -grad(f)^T d , under constraint
// if alpha_i == C, d != +1
// if alpha_i == 0, d != -1
double Gmax1 = - INF; // max { -grad(f)_i * d | y_i = +1, d = +1 }
int Gmax1_idx = - 1;
double Gmax2 = - INF; // max { -grad(f)_i * d | y_i = +1, d = -1 }
int Gmax2_idx = - 1;
double Gmax3 = - INF; // max { -grad(f)_i * d | y_i = -1, d = +1 }
int Gmax3_idx = - 1;
double Gmax4 = - INF; // max { -grad(f)_i * d | y_i = -1, d = -1 }
int Gmax4_idx = - 1;
for (int i = 0; i < active_size; i++)
{
if (y[i] == + 1)
// y == +1
{
if (!is_upper_bound(i))
// d = +1
{
if (- G[i] > Gmax1)
{
Gmax1 = - G[i];
Gmax1_idx = i;
}
}
if (!is_lower_bound(i))
// d = -1
{
if (G[i] > Gmax2)
{
Gmax2 = G[i];
Gmax2_idx = i;
}
}
}
// y == -1
else
{
if (!is_upper_bound(i))
// d = +1
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