cyber_attack_classification.py 文件源码

def Encoding(data, general_matrix=None):
    encoder = LabelBinarizer()
    count = 0
    # encoding
    for i in range(data.shape[1]):
        if type(data[0, i]) == str:
            count += 1
            col = data[:, i]
            unique = np.unique(col if general_matrix is None else general_matrix[:, i])

            try:
                encoder.fit(unique)
            except:
                pass

            new_col = encoder.transform(col)

            # split at i and i + 1
            before, removed, after = np.hsplit(data, [i, i + 1])
            # concatenate
            data = np.concatenate((before, new_col, after), axis=1)
            before, removed, after = np.hsplit(general_matrix, [i, i + 1])
            general_matrix = np.concatenate((before, encoder.transform(general_matrix[:, i]), after), axis=1)

    print "count : %d" % count
    # return data
    return data