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namespace  data_parser


def data_parser.create_ROC
def data_parser.extract_data
def data_parser.process


list data_parser.ACT_LIST = ['WINCE', 'NOD', 'SHAKE', 'JOY', "FEAR", "SUPRISE", "ANGER", "DISGUST", "SADNESS"]
dictionary data_parser.ACTIONS
list data_parser.all_tpr = []
tuple data_parser.args = parser.parse_args()
tuple = StratifiedKFold(y, k=9)
 Code below modified from
dictionary data_parser.DEGREES
string = "One or more training data files to process"
string data_parser.label = 'Mean ROC (area = %0.2f)'
tuple data_parser.mean_auc = auc(mean_fpr, mean_tpr)
tuple data_parser.mean_fpr = np.linspace(0, 1, n_samples)
float data_parser.mean_tpr = 0.0
tuple data_parser.parser
tuple data_parser.probas_ =[train], y[train])
tuple data_parser.roc_auc = auc(fpr, tpr)

Author(s): Phillip M. Grice, Advisor: Prof. Charlie Kemp, Lab: The Healthcare Robotoics Lab at Georgia Tech.
autogenerated on Wed Nov 27 2013 11:57:42