def train_classifier_listing(self):
self.clfListing = GaussianNB()
files = self.b2s.ls('data/training')
X = np.zeros((len(files), self.numFeat))
Y = np.zeros(len(files))
for i, file in enumerate(files):
f = file['fileName']
# read json into feature vector
if not f.endswith('.json'):
continue
textJson = self.b2s.download(f)
listing = json.loads(textJson)
X[i] = self.bundle_json_obj(listing)
Y[i] = max(int(listing['price'] / 50), 10)
self.clfListing.fit(X, Y)
temp = tempfile.NamedTemporaryFile()
joblib.dump(self.clfListing, temp.name)
self.b2s.upload('classifiers/nb_listing.pkl',
temp.read(), 'application/octet-stream')
return self.clfListing.score(X, Y)
# train a classifier on description
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