void COnlineLibLinear::train_example(CStreamingDotFeatures *feature, float64_t label)
{
CStreamingDenseFeatures<float32_t> *feat =
dynamic_cast<CStreamingDenseFeatures<float32_t> *>(feature);
if (feat == NULL)
SG_ERROR("Expected streaming dense feature <float32_t>\n");
train_one(feat->get_vector(), label);
}
float32_t CStreamingDenseFeatures<T>::dot(CStreamingDotFeatures* df)
{
ASSERT(df);
ASSERT(df->get_feature_type() == get_feature_type());
ASSERT(df->get_feature_class() == get_feature_class());
CStreamingDenseFeatures<T>* sf = (CStreamingDenseFeatures<T>*) df;
SGVector<T> other_vector=sf->get_vector();
float32_t result = CMath::dot(current_vector, other_vector.vector, current_length);
return result;
}
