bool MeanSplit<BoundType, MatType>::SplitNode(const BoundType& bound,
MatType& data,
const size_t begin,
const size_t count,
size_t& splitDimension,
size_t& splitCol,
std::vector<size_t>& oldFromNew)
{
splitDimension = data.n_rows; // Indicate invalid.
double maxWidth = -1;
// Find the split dimension.
for (size_t d = 0; d < data.n_rows; d++)
{
double width = bound[d].Width();
if (width > maxWidth)
{
maxWidth = width;
splitDimension = d;
}
}
if (maxWidth == 0) // All these points are the same. We can't split.
return false;
// Split in the middle of that dimension.
double splitVal = bound[splitDimension].Mid();
// Perform the actual splitting. This will order the dataset such that points
// with value in dimension splitDimension less than or equal to splitVal are
// on the left of splitCol, and points with value in dimension splitDimension
// greater than splitVal are on the right side of splitCol.
splitCol = PerformSplit(data, begin, count, splitDimension, splitVal,
oldFromNew);
return true;
}
bool MeanSplit<BoundType, MatType>::SplitNode(const BoundType& bound,
MatType& data,
const size_t begin,
const size_t count,
size_t& splitCol,
std::vector<size_t>& oldFromNew)
{
size_t splitDimension = data.n_rows; // Indicate invalid.
double maxWidth = -1;
// Find the split dimension. If the bound is tight, we only need to consult
// the bound's width.
if (bound::BoundTraits<BoundType>::HasTightBounds)
{
for (size_t d = 0; d < data.n_rows; d++)
{
const double width = bound[d].Width();
if (width > maxWidth)
{
maxWidth = width;
splitDimension = d;
}
}
}
else
{
// We must individually calculate bounding boxes.
math::Range* ranges = new math::Range[data.n_rows];
for (size_t i = begin; i < begin + count; ++i)
{
// Expand each dimension as necessary.
for (size_t d = 0; d < data.n_rows; ++d)
{
const double val = data(d, i);
if (val < ranges[d].Lo())
ranges[d].Lo() = val;
if (val > ranges[d].Hi())
ranges[d].Hi() = val;
}
}
// Now, which is the widest?
for (size_t d = 0; d < data.n_rows; d++)
{
const double width = ranges[d].Width();
if (width > maxWidth)
{
maxWidth = width;
splitDimension = d;
}
}
delete[] ranges;
}
if (maxWidth == 0) // All these points are the same. We can't split.
return false;
// Split in the mean of that dimension.
double splitVal = 0.0;
for (size_t i = begin; i < begin + count; ++i)
splitVal += data(splitDimension, i);
splitVal /= count;
Log::Assert(splitVal >= bound[splitDimension].Lo());
Log::Assert(splitVal <= bound[splitDimension].Hi());
// Perform the actual splitting. This will order the dataset such that points
// with value in dimension splitDimension less than or equal to splitVal are
// on the left of splitCol, and points with value in dimension splitDimension
// greater than splitVal are on the right side of splitCol.
splitCol = PerformSplit(data, begin, count, splitDimension, splitVal,
oldFromNew);
return true;
}
