void Learner1::PredictAll(
const Data& data,
const T_VECTOR& data_dist,
T_VECTOR& result,
float& error
)
{
error = 0.0;
size_t data_len = data.m_data.size();
for ( size_t i = 0; i < data_len; ++i )
{
//todo check valid dimension
T_DTYPE value = data.m_data[i][m_best_dimension];
if (m_learn_type == ">" )
{
if ( value > m_splitter )
result.push_back(1);
else
result.push_back(-1);
}
else if (m_learn_type == "<=" )
{
if ( value <= m_splitter )
result.push_back(1);
else
result.push_back(-1);
}
else
{
std::cerr << "error: not a valid learn type," << m_learn_type << endl;
assert(0);
}
T_DTYPE label = result[ result.size() - 1 ];
if (label*data.m_target[i] < 0)
{
//predict error
error += 1 * data_dist[i];
}
}
}
