BlackBoxAuditing/model_factories/SVM.py
def list_to_tf_input(data, response_index, num_outcomes):
  """
  Separates the outcome feature from the data.
  """
  matrix = np.matrix([row[:response_index] + row[response_index+1:] for row in data])
  outcomes = np.asarray([row[response_index] for row in data], dtype=np.uint8)

  return matrix, outcomes
def list_to_tf_input(data, response_index, num_outcomes):
  matrix = np.matrix([row[:response_index] + row[response_index+1:] for row in data])
  outcomes = np.asarray([row[response_index] for row in data], dtype=np.uint8)

  return matrix, outcomes
def list_to_tf_input ( data , response_index , num_outcomes ) : matrix = np . matrix ( [ row [ : response_index ] + row [ response_index + 1 : ] for row in data ] ) outcomes = np . asarray ( [ row [ response_index ] for row in data ] , dtype = np . uint8 ) return matrix , outcomes
Separates the outcome feature from the data.
Separates the outcome feature from the data .