#!/usr/bin/env python
# coding: utf-8

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import sklearn


# # Multi-class Classification

# In[2]:


import scipy.io
data = scipy.io.loadmat('ex3data1.mat')


# In[3]:


# pick random 100 handwriting
import random
indexes = random.sample(range(0, 5000), 100)

figure = plt.figure(figsize=(10, 10))
for index, i in enumerate(indexes):
    plt.subplot(10, 10, index + 1)
    plt.axis('off')
    plt.imshow(data['X'][i].reshape(20, 20).transpose(), cmap='Greys')
    
plt.show()


# In[4]:


from sklearn.multiclass import OneVsRestClassifier
from sklearn.linear_model import LogisticRegression


# In[5]:


clf = OneVsRestClassifier(LogisticRegression(penalty='l2', C=1))
clf.fit(data['X'], data['y'])

print clf.score(data['X'], data['y'])


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