SVM multilabel classifier with letter recognition data example

Letter recognition data has been used from the UCI machine learning repository for illustration purposes using SVM classifiers. The link for downloading the data is here: https://archive.ics.uci.edu/ml/datasets/letter+recognition. The task is to identify each of a large number of black and white rectangular pixel displays as one of the 26 capital letters in the English alphabet (from A to Z; 26 classes altogether) based on a few characteristics in integers, such as x-box (horizontal position of box), y-box (vertical position of box), width of the box, height of the box, and so on:

>>> import os 
""" First change the following directory link to where all input files do exist """ 
>>> os.chdir("D:\\Book writing\\Codes\\Chapter 6") 
 
>>> import pandas as pd 
>>> letterdata = pd.read_csv("letterdata.csv") 
>>> print (letterdata.head())

Following code is used to remove the target variable...