def classify(self):
for i, x in enumerate(self.channel_decode):
feature_obj = Features(self.data_raw[int(x) - 1],
self.sampling_freq, self.features_id)
features = feature_obj.extract_features()
try:
prediction = self.clf[i].predict([features]) - 1
if prediction != (self.prediction >> i
& 1): # if prediction changes
self.prediction = self.output(i, prediction,
self.prediction)
print('Prediction: %s' % format(self.prediction, 'b'))
except ValueError:
print('prediction failed...')
