public void BuildTree()
{
if (errors == null) return;
int i = 0;
int max_branching = int.MaxValue;
double current_error = errors[errors.Length - 1];
int f = 0;
int length = ts.Length;
int len = 0;
int best_f = 0;
double best_cost = double.MaxValue;
for (i = 0; i < ts.freq.Length; i++)
{
f = ts.freq[i];
if (f == 0) continue;
for (; ; )
{
ModelSet s = new ModelSet(ts);
s.getModels(f, current_error, ref len);
//
if ((len >= Global.confidence * length) && (s.models.Length <= max_branching))
{
double cost = s.Cost();
if (cost < best_cost)
{
best_f = f;
best_cost = cost;
}
}
else break;
f = f * 2;
if (len == 0) break;
if ((i + 1 < ts.freq.Length) && (f > ts.freq[i + 1])) break;
}
}
Console.WriteLine(best_f);
if (best_f != 0) { setModels(best_f, errors, 1, 0); }
else
{
int done = 0;
for (; ; )
{
ModelSet s = new ModelSet(ts);
s.getModels(f, current_error, ref len);
if (s.models.Length >= max_branching)
{
f = f * 2;
}
else { best_f = f; if (s.models.Length == 1) done = 1; break; }
}
setModels(best_f, errors, 0, done);
}
//Set();
}
public void BuildTree()
{
if (errors == null)
{
return;
}
int i = 0;
int max_branching = int.MaxValue;
double current_error = errors[errors.Length - 1];
int f = 0;
int length = ts.Length;
int len = 0;
int best_f = 0;
double best_cost = double.MaxValue;
for (i = 0; i < ts.freq.Length; i++)
{
f = ts.freq[i];
if (f == 0)
{
continue;
}
for (; ;)
{
ModelSet s = new ModelSet(ts);
s.getModels(f, current_error, ref len);
//
if ((len >= Global.confidence * length) && (s.models.Length <= max_branching))
{
double cost = s.Cost();
if (cost < best_cost)
{
best_f = f;
best_cost = cost;
}
}
else
{
break;
}
f = f * 2;
if (len == 0)
{
break;
}
if ((i + 1 < ts.freq.Length) && (f > ts.freq[i + 1]))
{
break;
}
}
}
Console.WriteLine(best_f);
if (best_f != 0)
{
setModels(best_f, errors, 1, 0);
}
else
{
int done = 0;
for (; ;)
{
ModelSet s = new ModelSet(ts);
s.getModels(f, current_error, ref len);
if (s.models.Length >= max_branching)
{
f = f * 2;
}
else
{
best_f = f; if (s.models.Length == 1)
{
done = 1;
}
break;
}
}
setModels(best_f, errors, 0, done);
}
//Set();
}