void ml::TakeLabelCensus(const RowList & Examples,
map<int, size_t> & LabelCensus, size_t LabelAttributes,
int LCValue)
{
ml::GenericTakeLabelCensus<RowList::const_iterator, int>
(Examples.begin(), Examples.end(), LabelCensus, LabelAttributes,
LCValue);
}
void ml::TakeFeatureCensus(const RowList & Examples,
map<size_t, map<double, size_t> > & FeatureCensus,
const std::vector< std::pair<size_t, double> > & FeatureAttributes)
{
typedef typename std::map<double,size_t>::iterator CensusIterator;
FeatureCensus.clear();
// set non-nominal census to expected, the count to 0, and
// otherwise zero-out the nominal census.
for (int i = 0; i < FeatureAttributes.size(); i++)
{
if (FeatureAttributes[i].first != 0)
{
for (int j = 0; j < FeatureAttributes[i].first; j++)
{
FeatureCensus[i][(double)j] = 0u;
}
}
}
for (RowListCIterator Row = Examples.begin();
Row != Examples.end();
Row++)
{
for (int i = 0; i < FeatureAttributes.size(); i++)
{
if (FeatureAttributes[i].first == 0)
{
continue;
}
if (Row->first->at(i) == UNKNOWN_VALUE)
{
FeatureCensus[i][FeatureAttributes[i].second]++;
}
else
{
FeatureCensus[i][Row->first->at(i)]++;
}
}
}
}
