Trending Technology Machine Learning, Artificial Intelligent, Block Chain, IoT, DevOps, Data Science

Recent Post

Codecademy Code Foundations

Search This Blog

Handwritten Digit Recognition Project in Machine Learning

The dataset which we are going to use is made up of 1797 8𝗑8 images. Each image is of a hand-written digit.

In order to utilize an 8𝗑8 figure, we have to first transform it into a feature vector with length 64.

We will be using Super Vector Machine (SVM).

Plot 8𝗑8 image

# Import dataset
from om sklearn.datasets import load_digits

# Import the sklearn for SVM
from sklearn import svm

digits = load_digits( )

# Each datapoint is a 8𝗑8 image of digit
# Plot the image
plt.gray( )
plt.matshow(digits.image[20])
plt.show


Print the 8𝗑8 array which represents each pixel

print digits.images [20]
' ' '

Output :-
[ [  0.    0.     3.    13.    11.    7.     0.    0.]
  [  0.    0.     11.   16.    16.  16.     2.   0.]
  [  0.    4.     16.    9.      1.    14.    2.   0.]
  [  0.    4.     16.    0.      0.    16.    2.   0.]
  [  0.    0.     16.    1.      0.     12.   8.   0.]
  [  0.    0.     15.    9.      0.     13.   6.   0.]
  [  0.    0.      9.    14.     9.     14.   1.   0.]
  [  0.    0.      2.    12.     13.    4.    0.   0.]
' ' '

Train and Test the model

clf = svm.SVC( )
#  Train the model
clf.fit (digits.data[:-1], digits.target[ :-1])

# Test the model
  prediction = clf.predict(digits.data[20:21])

print  "Predicted Digit  ->" , prediction
' ' '

Output :
Predicted Digit  ->  [0]
' ' '

No comments:

Post a Comment

Popular Posts