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comparison deep/stacked_dae/v_sylvain/nist_apriori_error.py @ 439:5ca2936f2062

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Bug fix in per-class a priori error : should be lower than before for both upper and lower
author Guillaume Sicard <guitch21@gmail.com>
date Mon, 03 May 2010 09:42:36 -0400
parents fb028b37ce92
children b2a7d93caa0f
comparison
equal deleted inserted replaced
438:a6d339033d03 439:5ca2936f2062
1 # -*- coding: utf-8 -*-
1 __docformat__ = 'restructedtext en' 2 __docformat__ = 'restructedtext en'
2 3
3 import pdb 4 import pdb
4 import numpy 5 import numpy
5 from numpy import array 6 from numpy import array
63 print('Number of layers not implemented yet, please do it') 64 print('Number of layers not implemented yet, please do it')
64 65
65 66
66 total_error_count=0 67 total_error_count=0
67 total_exemple_count=0 68 total_exemple_count=0
69 total_error_count_wap=0
70
68 if part == 0: 71 if part == 0:
69 iter = dataset.train(1) 72 iter = dataset.train(1)
70 if part == 1: 73 if part == 1:
71 iter = dataset.valid(1) 74 iter = dataset.valid(1)
72 if part == 2: 75 if part == 2:
109 ## for i in xrange(len(out_act[0])): 112 ## for i in xrange(len(out_act[0])):
110 ## out[i]=sigmoid(array(out_act[0,i])) 113 ## out[i]=sigmoid(array(out_act[0,i]))
111 114
112 #get grouped based error 115 #get grouped based error
113 #with a priori 116 #with a priori
114 if(y>9 and y<35): 117 if(y>9 and y<36):
115 predicted_class=numpy.argmax(out[0,10:35])+10 118 predicted_class=numpy.argmax(out[0,10:36])+10
116 if(predicted_class!=y): 119 if(predicted_class!=y):
117 total_error_count+=1 120 total_error_count+=1
118 121
119 if(y<10): 122 if(y<10):
120 predicted_class=numpy.argmax(out[0,0:10]) 123 predicted_class=numpy.argmax(out[0,0:10])
121 if(predicted_class!=y): 124 if(predicted_class!=y):
122 total_error_count+=1 125 total_error_count+=1
123 if(y>34): 126 if(y>35):
124 predicted_class=numpy.argmax(out[0,35:])+35 127 predicted_class=numpy.argmax(out[0,36:])+36
125 if(predicted_class!=y): 128 if(predicted_class!=y):
126 total_error_count+=1 129 total_error_count+=1
127 130 #without a priori
131 predicted_class=numpy.argmax(out)
132 if(predicted_class!=y):
133 total_error_count_wap+=1
134
128 print '\t total exemples count: '+str(total_exemple_count) 135 print '\t total exemples count: '+str(total_exemple_count)
129 print '\t total error count: '+str(total_error_count) 136 print '\t total error count: '+str(total_error_count)
130 print '\t percentage of error: '+str(total_error_count*100.0/total_exemple_count*1.0)+' %' 137 print '\t percentage of error: '+str(total_error_count*100.0/total_exemple_count*1.0)+' %'
138 print '\t total error count without a priori: '+str(total_error_count_wap)
139 print '\t percentage of error without a priori: '+str(total_error_count_wap*100.0/total_exemple_count*1.0)+' %'
131 140
132 141
133 def sigmoid(value): 142 def sigmoid(value):
134 ## if len(value) > 1: 143 ## if len(value) > 1:
135 ## retour = numpy.zeros(len(value),float) 144 ## retour = numpy.zeros(len(value),float)