Sha256: e83e8b66ca86f67690dc9d72baaeabd6ba70678ad0428e795cf1b0b1c884d51d
Contents?: true
Size: 1.35 KB
Versions: 6
Compression:
Stored size: 1.35 KB
Contents
#include "model.h" void Model::Model::train(DataSet::Example *example) { } void Model::Model::train_text(string text) { } DataSet::Example *Model::Model::process_text(string text, bool create_features) { return text_pipeline->process_text((DataSet::SparseDataSet *)data_set, (char *)text.c_str(), create_features); } void Model::Model::add_text_example(string text, string category) { DataSet::Example *example = text_pipeline->process_text((DataSet::SparseDataSet *)data_set, (char *)text.c_str(), true); example->set_category_index(data_set, data_set->category_feature()->value_index(category)); } int Model::Model::classify(DataSet::Example *example) { return classifier->classify(example); } int Model::Model::classify_text(string text) { DataSet::SparseExample *example = text_pipeline->process_text((DataSet::SparseDataSet *)data_set, (char *)text.c_str(), false); int category = classifier->classify(example); delete example; return category; } vector<Classifier::Score> *Model::Model::rank(DataSet::Example *example) { return classifier->rank(example); } vector<Classifier::Score> *Model::Model::rank_text(string text) { DataSet::SparseExample *example = text_pipeline->process_text((DataSet::SparseDataSet *)data_set, (char *)text.c_str(), false); vector<Classifier::Score> *ranks = classifier->rank(example); delete example; return ranks; }
Version data entries
6 entries across 6 versions & 1 rubygems