cs596-029-week-2-report

week-2-result.py

$ python recognize_faces.py 

======LOAD TRAINING DATA=======
- Mode, id, name, total images: training, 01, Tracy, 162
- Mode, id, name, total images: training, 02, Trish, 68
- Mode, id, name, total images: training, 03, Steven, 64

======LOAD TESTING DATA=======
- Mode, id, name, total images: testing, 00, friends, 0
- Mode, id, name, total images: testing, 01, Tracy, 28
- Mode, id, name, total images: testing, 02, Trish, 30
- Mode, id, name, total images: testing, 03, Steven, 13

======FITTING THE CLASSIFIER TO THE TRAINING SET=======
Done in 0.761 second(s).
Best estimator found by grid search: SVC(C=1000.0, cache_size=200, class_weight='auto', coef0=0.0, degree=3,
  gamma=0.01, kernel='rbf', max_iter=-1, probability=False,
  random_state=None, shrinking=True, tol=0.001, verbose=False)

==================RESULT==================
Confusion Matrix: 
        Tracy  Trish  Steven
Tracy      27      1       0
Trish      10     20       0
Steven      1      0      12
Classification Report: 
             precision    recall  f1-score   support

      Tracy       0.71      0.96      0.82        28
      Trish       0.95      0.67      0.78        30
     Steven       1.00      0.92      0.96        13

avg / total       0.87      0.83      0.83        71


        How to comprehend the report:
        - Recall value: "Given a true face of person X, how likely does the classifier detect it is X?
        - Precision value: "If the classifier predicted a face person X, how likely is it to be correct?