def kerperceptron_batch(data, labels, sigma_squared=25.0):
    c = np.zeros(len(data)).astype('float')
    i, t = 0, 0
    batches = list()

    while (i < 10):
        t = 0
        for image in data:
            if (t == 0):
                numerrors = 0
                currerrors = np.zeros(len(data)).astype('int')
                batches.append(currerrors)

            y = int(summation_kernel(c,t,data, sigma_squared) >= 0)

            if (y == 0) and (labels[t] == 1):
                c[t] += 1
                numerrors += 1
            elif (y == 1) and (labels[t] == -1):
                c[t] -= -1
                numerrors += 1

            currerrors[t] = numerrors
            t += 1

        i += 1

    batches = np.array(batches)
    return c, batches, i