Esempio n. 1
0
def get_args(filename, sd, bn, im):
    x = ArffToArgs()
    x.set_input(filename)
    x.set_class_index("last")

    x.set_impute(im)
    x.set_binarize(bn)
    x.set_standardize(sd)

    args = x.get_args()
    x.close()
    return args
def get_args(filename, sd, bn, im):
    x = ArffToArgs()
    x.set_input(filename)
    x.set_class_index("last")

    x.set_impute(im)
    x.set_binarize(bn)
    x.set_standardize(sd)

    args = x.get_args()
    x.close()
    return args
        bs = args["batch_size"]
    else:
        bs = 128

    X_test = args["X_test"]

    preds = iter_test(X_test).tolist()

    new = []
    for pred in preds:
        new.append(np.eye(args["num_classes"])[pred].tolist())
    return new


if __name__ == '__main__':
    x = ArffToArgs()
    x.set_input("data/cpu_act.arff")
    x.set_class_index("last")
    x.set_impute(True)
    x.set_binarize(True)
    x.set_standardize(True)
    x.set_arguments(
        "adaptive=True;alpha=0.01;lambda=0;epochs=500;rmsprop=True")
    args = x.get_args()
    #args["debug"] = True

    args["X_test"] = np.asarray(args["X_train"], dtype="float32")

    model = train(args)

    test(args, model)
    if "batch_size" in args:
        bs = args["batch_size"]
    else:
        bs = 128

    X_test = args["X_test"]

    preds = iter_test(X_test).tolist()

    new = []
    for pred in preds:
        new.append( np.eye(args["num_classes"])[pred].tolist() )
    return new

if __name__ == '__main__':
    x = ArffToArgs()
    x.set_input("data/cpu_act.arff")
    x.set_class_index("last")
    x.set_impute(True)
    x.set_binarize(True)
    x.set_standardize(True)
    x.set_arguments("adaptive=True;alpha=0.01;lambda=0;epochs=500;rmsprop=True")
    args = x.get_args()
    #args["debug"] = True

    args["X_test"] = np.asarray(args["X_train"], dtype="float32")

    model = train(args)

    test(args, model)