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util_precision.py
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util_precision.py
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####################################################################
# This small utility read labels true value the test set input file
# and the predicted score from logistic regression output and
# calculate accuracy, recall and precision
####################################################################
import sys
import string
import numpy as np
from sklearn.metrics import precision_score,recall_score,accuracy_score
def main():
if len(sys.argv) != 3:
print 'usage: ./util.py file'
sys.exit(1)
filename = sys.argv[1]
filename1 = sys.argv[2]
input_file = open(filename, 'r')
input_file1 = open(filename1, 'r')
y_true = []
i = 0
for line in input_file:
click = int(line.split(',')[1])
y_true.append(click)
i = i + 1
print "read",i,"lines"
y_trueA = np.array(y_true)
y_pred = []
i = 0
for line in input_file1:
click = int(float(line.split(',')[1])/0.5)
y_pred.append(click)
i = i + 1
print "read",i,"lines"
y_predA = np.array(y_pred)
print "precision score is:"
print precision_score(y_trueA, y_predA)
print "recall score is:"
print recall_score(y_trueA, y_predA)
print "accuracy score is:"
print accuracy_score(y_trueA, y_predA)
if __name__ == '__main__':
main()