def test_drop_intents_below_freq():
td = training_data.load_data('data/examples/rasa/demo-rasa.json')
clean_td = drop_intents_below_freq(td, 0)
assert clean_td.intents == {'affirm', 'goodbye', 'greet', 'restaurant_search'}
clean_td = drop_intents_below_freq(td, 10)
assert clean_td.intents == {'affirm', 'restaurant_search'}
def test_drop_intents_below_freq():
td = training_data.load_data('data/examples/rasa/demo-rasa.json')
clean_td = drop_intents_below_freq(td, 0)
assert clean_td.intents == {'affirm', 'goodbye', 'greet',
'restaurant_search'}
clean_td = drop_intents_below_freq(td, 10)
assert clean_td.intents == {'affirm', 'restaurant_search'}
def cross_validation(data_path, config_path):
# same as rasa_nlu's evaluate interface
data = training_data.load_data(data_path)
data = drop_intents_below_freq(data, cutoff=5)
# same as rasa_nlu's evaluate interface
default_folds = 10
# same as rasa_nlu's evaluate interface
nlu_config = config.load(config_path)
intent_results, entity_results = run_cv_evaluation(data, default_folds,
nlu_config)
template_result = {
'intent': {
'train': {},
'test': {}
},
'entity': {
'train': {},
'test': {}
},
}
set_template_result(intent_results.train,
template_result['intent']['train'])
set_template_result(intent_results.test, template_result['intent']['test'])
set_template_result(entity_results.train.values()[0],
template_result['entity']['train'])
set_template_result(entity_results.test.values()[0],
template_result['entity']['test'])
return template_result
