2ab8c1444facbd46df8767a5badda5b9f1a50c29,tpot/tpot.py,,main,#,741

Before Change

            print("{}\t=\t{}".format(arg, args.__dict__[arg]))
        print("")

    input_data = pd.read_csv(args.INPUT_FILE, sep=args.INPUT_SEPARATOR)

    if "Class" in input_data.columns.values:
        input_data.rename(columns={"Class": "class"}, inplace=True)

    training_indices, testing_indices = train_test_split(input_data.index,
                                                         stratify=input_data["class"].values,
                                                         train_size=0.75,
                                                         test_size=0.25,
                                                         random_state=args.RANDOM_STATE)

    training_features = input_data.loc[training_indices].drop("class", axis=1).values
    training_classes = input_data.loc[training_indices, "class"].values

    testing_features = input_data.loc[testing_indices].drop("class", axis=1).values
    testing_classes = input_data.loc[testing_indices, "class"].values

    tpot = TPOT(generations=args.GENERATIONS, population_size=args.POPULATION_SIZE,
                mutation_rate=args.MUTATION_RATE, crossover_rate=args.CROSSOVER_RATE,

After Change

        print("")

    input_data = np.recfromcsv("PATH/TO/DATA/FILE", sep="COLUMN_SEPARATOR")
    features = input_data.view((np.float64, len(input_data.dtype.names)))
    np.delete(features, input_data.dtype.names.index("class"))

    training_features, testing_features, training_classes, testing_classes = \

Instances