Machine Learning for Beginners in Python: Loading scikit-learn’s Digits Dataset

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Loading scikit-learn’s Digits Dataset

Preliminaries

# Load libraries
from sklearn import datasets
import matplotlib.pyplot as plt

Load Digits Dataset

Digits is a dataset of handwritten digits. Each feature is the intensity of one pixel of an 8 x 8 image.

# Load digits dataset
digits = datasets.load_digits()

# Create feature matrix
X = digits.data

# Create target vector
y = digits.target

# View the first observation's feature values
X[0]
array([  0.,   0.,   5.,  13.,   9.,   1.,   0.,   0.,   0.,   0.,  13.,
        15.,  10.,  15.,   5.,   0.,   0.,   3.,  15.,   2.,   0.,  11.,
         8.,   0.,   0.,   4.,  12.,   0.,   0.,   8.,   8.,   0.,   0.,
         5.,   8.,   0.,   0.,   9.,   8.,   0.,   0.,   4.,  11.,   0.,
         1.,  12.,   7.,   0.,   0.,   2.,  14.,   5.,  10.,  12.,   0.,
         0.,   0.,   0.,   6.,  13.,  10.,   0.,   0.,   0.])

The observation’s feature values are presented as a vector. However, by using the images method we can load the the same feature values as a matrix and then visualize the actual handwritten character:

# View the first observation's feature values as a matrix
digits.images[0]
array([[  0.,   0.,   5.,  13.,   9.,   1.,   0.,   0.],
       [  0.,   0.,  13.,  15.,  10.,  15.,   5.,   0.],
       [  0.,   3.,  15.,   2.,   0.,  11.,   8.,   0.],
       [  0.,   4.,  12.,   0.,   0.,   8.,   8.,   0.],
       [  0.,   5.,   8.,   0.,   0.,   9.,   8.,   0.],
       [  0.,   4.,  11.,   0.,   1.,  12.,   7.,   0.],
       [  0.,   2.,  14.,   5.,  10.,  12.,   0.,   0.],
       [  0.,   0.,   6.,  13.,  10.,   0.,   0.,   0.]])
# Visualize the first observation's feature values as an image
plt.gray() 
plt.matshow(digits.images[0]) 
plt.show()
<matplotlib.figure.Figure at 0x1068494a8>

png

 

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