/home/heimdall/anaconda3/bin/python /mnt/attic/Projects/normimages/newMethod/stdData.py
Extracting the top 150 eigenfaces from 1702 faces
/home/heimdall/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:58: DeprecationWarning: Class RandomizedPCA is deprecated; RandomizedPCA was deprecated in 0.18 and will be removed in 0.20. Use PCA(svd_solver='randomized') instead. The new implementation DOES NOT store whiten ``components_``. Apply transform to get them.
  warnings.warn(msg, category=DeprecationWarning)
done in 2.670s
Projecting the input data on the eigenfaces orthonormal basis
done in 0.524s
Fitting the classifier to the training set
done in 73.977s
Best estimator found by grid search:
SVC(C=1000.0, cache_size=200, class_weight=None, coef0=0.0,
  decision_function_shape='ovr', degree=3, gamma=0.0001, kernel='rbf',
  max_iter=-1, probability=False, random_state=None, shrinking=True,
  tol=0.001, verbose=False)
samples in train data (1702, 16384)
             precision    recall  f1-score   support

    akshada       1.00      1.00      1.00       184
    ashvini       1.00      1.00      1.00       179
    deepali       1.00      1.00      1.00       169
 geetanjali       1.00      1.00      1.00       169
       maam       1.00      1.00      1.00        93
    prerana       1.00      1.00      1.00       180
    radhika       1.00      1.00      1.00        38
     ravina       1.00      1.00      1.00       175
     shweta       1.00      1.00      1.00       170
     snehal       1.00      1.00      1.00       170
     sujata       1.00      1.00      1.00       175

avg / total       1.00      1.00      1.00      1702

[[184   0   0   0   0   0   0   0   0   0   0]
 [  0 179   0   0   0   0   0   0   0   0   0]
 [  0   0 169   0   0   0   0   0   0   0   0]
 [  0   0   0 169   0   0   0   0   0   0   0]
 [  0   0   0   0  93   0   0   0   0   0   0]
 [  0   0   0   0   0 180   0   0   0   0   0]
 [  0   0   0   0   0   0  38   0   0   0   0]
 [  0   0   0   0   0   0   0 175   0   0   0]
 [  0   0   0   0   0   0   0   0 170   0   0]
 [  0   0   0   0   0   0   0   0   0 170   0]
 [  0   0   0   0   0   0   0   0   0   0 175]]




samples in test data (568, 16384)
             precision    recall  f1-score   support

    akshada       1.00      1.00      1.00        50
    ashvini       1.00      1.00      1.00        55
    deepali       1.00      1.00      1.00        65
 geetanjali       1.00      1.00      1.00        65
       maam       1.00      1.00      1.00        28
    prerana       1.00      1.00      1.00        54
    radhika       1.00      1.00      1.00         5
     ravina       1.00      1.00      1.00        59
     shweta       1.00      1.00      1.00        64
     snehal       1.00      1.00      1.00        64
     sujata       1.00      1.00      1.00        59

avg / total       1.00      1.00      1.00       568

[[50  0  0  0  0  0  0  0  0  0  0]
 [ 0 55  0  0  0  0  0  0  0  0  0]
 [ 0  0 65  0  0  0  0  0  0  0  0]
 [ 0  0  0 65  0  0  0  0  0  0  0]
 [ 0  0  0  0 28  0  0  0  0  0  0]
 [ 0  0  0  0  0 54  0  0  0  0  0]
 [ 0  0  0  0  0  0  5  0  0  0  0]
 [ 0  0  0  0  0  0  0 59  0  0  0]
 [ 0  0  0  0  0  0  0  0 64  0  0]
 [ 0  0  0  0  0  0  0  0  0 64  0]
 [ 0  0  0  0  0  0  0  0  0  0 59]]

Process finished with exit code 0