def train_models():
models = dict()
if settings["models"]["msda"]:
dims = settings["dimensionalities"]["msda"]
try:
msda = mSDA.load("reuters_msda_%sdims" % dims)
# the line below is for testing a model I have locally on my machine
#msda = mSDA.load("persist/mSDA/mSDA_wiki_dim-1000_stem-False_tfidf-False_noise-0.5_num_layers-3")
except:
ln.info("Training mSDA...")
prototype_ids = [id_ for id_, freq in sorted(dictionary.dfs.items(), key=lambda (k, v): v, reverse=True)[:dims]]
msda = mSDA(0.5, 5, len(dictionary), dims, prototype_ids=prototype_ids)
msda.train(bow_corpus())
msda.save("reuters_msda_%sdims" % dims)
msda.__out_size = dims
models["msda"] = msda
if settings["models"]["lsi"]:
dims = settings["dimensionalities"]["lsi"]
try:
lsi = LsiModel.load("reuters_lsi_%sdims" % dims)
except:
ln.info("Training LSI...")
lsi = LsiModel(corpus=bow_corpus(), num_topics=dims, id2word=dictionary)
lsi.save("reuters_lsi_%sdims" % dims)
lsi.__out_size = dims
models["lsi"] = lsi
return models
def train_models():
models = dict()
if settings["models"]["msda"]:
dims = settings["dimensionalities"]["msda"]
try:
msda = mSDA.load("reuters_msda_%sdims" % dims)
# the line below is for testing a model I have locally on my machine
#msda = mSDA.load("persist/mSDA/mSDA_wiki_dim-1000_stem-False_tfidf-False_noise-0.5_num_layers-3")
except:
ln.info("Training mSDA...")
prototype_ids = [
id_ for id_, freq in sorted(dictionary.dfs.items(),
key=lambda (k, v): v,
reverse=True)[:dims]
]
msda = mSDA(0.5,
5,
len(dictionary),
dims,
prototype_ids=prototype_ids)
msda.train(bow_corpus())
msda.save("reuters_msda_%sdims" % dims)
msda.__out_size = dims
models["msda"] = msda
if settings["models"]["lsi"]:
dims = settings["dimensionalities"]["lsi"]
try:
lsi = LsiModel.load("reuters_lsi_%sdims" % dims)
except:
ln.info("Training LSI...")
lsi = LsiModel(corpus=bow_corpus(),
num_topics=dims,
id2word=dictionary)
lsi.save("reuters_lsi_%sdims" % dims)
lsi.__out_size = dims
models["lsi"] = lsi
return models
