def get_bow_cfg():
toreturn = {}
cfg = combinator.get_classifier_technique_config(bow=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
return toreturn
def get_bow_rating_sentiment1_cfg(key_prefix):
toreturn = {}
cfg = combinator.get_classifier_technique_config(bow=True, rating=True, sentiment1=True)
key = key_prefix + "__" + combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
return toreturn
def get_bow_rating_tense_sentiment1_cfg():
toreturn = {}
cfg = combinator.get_classifier_technique_config(bow=True, rating=True, tense=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
return toreturn
def get_combined_cfgs_journal_version():
toreturn = {}
cfg = combinator.get_classifier_technique_config(bow=True,
lemmatize=True,
rating=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
rating=True,
sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
rating=True,
tense=True,
sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bigram=True,
rating=True,
sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bigram=True,
remove_stopwords=True,
lemmatize=True,
rating=True,
tense=True,
sentiment2=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
bigram=True,
tense=True,
sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
lemmatize=True,
bigram=True,
rating=True,
tense=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
remove_stopwords=True,
bigram=True,
rating=True,
tense=True,
sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
remove_stopwords=True,
lemmatize=True,
rating=True,
tense=True,
sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True,
remove_stopwords=True,
lemmatize=True,
rating=True,
tense=True,
sentiment2=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bow
cfg = combinator.get_classifier_technique_config(bow=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bigram
cfg = combinator.get_classifier_technique_config(bigram=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bow+bigram
cfg = combinator.get_classifier_technique_config(bow=True, bigram=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bow+lemmatize
cfg = combinator.get_classifier_technique_config(bow=True, lemmatize=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bow-stopwords
cfg = combinator.get_classifier_technique_config(bow=True,
remove_stopwords=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bow-stopwords+lemmatize
cfg = combinator.get_classifier_technique_config(bow=True,
remove_stopwords=True,
lemmatize=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
## add bow+bigram-stopwords+lemmatize
cfg = combinator.get_classifier_technique_config(bow=True,
bigram=True,
remove_stopwords=True,
lemmatize=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
return toreturn
def get_combined_cfgs_journal_version():
toreturn = {}
#Document classification (&NLP)
cfg = combinator.get_classifier_technique_config(bow=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bigram=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, bigram=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, lemmatize=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, remove_stopwords=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, lemmatize=True, remove_stopwords=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, bigram=True, remove_stopwords=True, lemmatize=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
#Metadata
cfg = combinator.get_classifier_technique_config(rating=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(rating=True, length=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(rating=True, length=True, tense=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(rating=True, length=True, tense=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(rating=True, length=True, tense=True, sentiment2=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
#Combined
cfg = combinator.get_classifier_technique_config(bow=True, lemmatize=True, rating=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, rating=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, rating=True, tense=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bigram=True, rating=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bigram=True, remove_stopwords=True, lemmatize=True, rating=True, tense=True, sentiment2=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, bigram=True, tense=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, lemmatize=True, bigram=True, rating=True, tense=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, remove_stopwords=True, bigram=True, rating=True, tense=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, remove_stopwords=True, lemmatize=True, rating=True, tense=True, sentiment1=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
cfg = combinator.get_classifier_technique_config(bow=True, remove_stopwords=True, lemmatize=True, rating=True, tense=True, sentiment2=True)
key = combinator.get_key_for_classifier_config(cfg)
toreturn[key] = cfg
return toreturn
