.. _example_plot_digits_classification.py:


================================
Recognizing hand-written digits
================================

An example showing how the scikit-learn can be used to recognize images of
hand-written digits.

This example is commented in the
:ref:`tutorial section of the user manual <getting_started>`.




.. image:: images/plot_digits_classification_1.png
    :align: center


**Script output**::

  Classification report for classifier SVC(C=100, cache_size=200, class_weight=None, coef0=0.0, degree=3,
    gamma=0.001, kernel=rbf, probability=False, scale_C=True, shrinking=True,
    tol=0.001):
               precision    recall  f1-score   support
  
            0       1.00      0.98      0.99        88
            1       0.93      0.92      0.93        91
            2       0.98      0.93      0.95        86
            3       0.95      0.81      0.88        91
            4       0.99      0.92      0.96        92
            5       0.88      0.90      0.89        91
            6       0.99      0.99      0.99        91
            7       0.95      1.00      0.97        89
            8       0.91      0.84      0.88        88
            9       0.75      0.96      0.84        92
  
  avg / total       0.93      0.93      0.93       899
  
  
  Confusion matrix:
  [[86  0  0  0  1  1  0  0  0  0]
   [ 0 84  0  0  0  1  0  0  0  6]
   [ 0  0 80  3  0  0  0  0  0  3]
   [ 0  0  0 74  0  4  0  4  5  4]
   [ 0  0  0  0 85  0  0  1  2  4]
   [ 0  0  0  0  0 82  1  0  0  8]
   [ 0  1  0  0  0  0 90  0  0  0]
   [ 0  0  0  0  0  0  0 89  0  0]
   [ 0  5  2  0  0  2  0  0 74  5]
   [ 0  0  0  1  0  3  0  0  0 88]]



**Python source code:** :download:`plot_digits_classification.py <plot_digits_classification.py>`

.. literalinclude:: plot_digits_classification.py
    :lines: 13-