Python compute_idfの例

コード例 #1

ファイル: similarity.py プロジェクト: lovingmage/ART4SQLi

def feature(PATH):

	#filename = './fuzzdb/attack-payloads/sql-injection/detect/MySQL.fuzz.txt'
	filename = PATH
	test_case_list = file_operation.fileopt_line(filename)
	full_list = file_operation.fileopt_all(filename)
	full_stat_list = testcase_stat.stat_all(full_list)
	test_case_stat_list = testcase_stat.stat(test_case_list)
	tf_matrix = testcase_stat.compute_tf(test_case_stat_list)
	test_case_stat_list = testcase_stat.stat(test_case_list)
	idf_matrix = testcase_stat.compute_idf(test_case_stat_list, full_stat_list)
	tf_idf_list = testcase_stat.compute_tf_idf(tf_matrix, idf_matrix)
	test_case_feature_list = testcase_stat.feature_vector_quantify(tf_idf_list, full_stat_list)

	return test_case_feature_list

コード例 #2

ファイル: test_case_feature.py プロジェクト: Neroli1108/ART4SQLi

#print test_case_stat_list

tf_matrix = testcase_stat.compute_tf(test_case_stat_list)
#computing tf value and store in tf_matrix 
#print tf_matrix

#Important this place
# In this place we should recompute the test_case_stat_list value
# If not the consequence will go wrong

test_case_stat_list = testcase_stat.stat(test_case_list)

#print test_case_stat_list
# Recompute the test_case_stat_list and then compute the idf value

idf_matrix = testcase_stat.compute_idf(test_case_stat_list, full_stat_list)

#print idf_matrix

#combine tf_matrix and idf_matrix
#Compute tf_idf_list

tf_idf_list = testcase_stat.compute_tf_idf(tf_matrix, idf_matrix)

#print tf_idf_list

#Put them into feature vector and store in 
#test_case_feature_list
#----------------------------------------------------------------------------------------------
test_case_feature_list = testcase_stat.feature_vector_quantify(tf_idf_list, full_stat_list)
#----------------------------------------------------------------------------------------------

コード例 #3

ファイル: test_case_feature.py プロジェクト: lovingmage/ART4SQLi

#print test_case_stat_list

tf_matrix = testcase_stat.compute_tf(test_case_stat_list)
#computing tf value and store in tf_matrix
#print tf_matrix

#Important this place
# In this place we should recompute the test_case_stat_list value
# If not the consequence will go wrong

test_case_stat_list = testcase_stat.stat(test_case_list)

#print test_case_stat_list
# Recompute the test_case_stat_list and then compute the idf value

idf_matrix = testcase_stat.compute_idf(test_case_stat_list, full_stat_list)

#print idf_matrix

#combine tf_matrix and idf_matrix
#Compute tf_idf_list

tf_idf_list = testcase_stat.compute_tf_idf(tf_matrix, idf_matrix)

#print tf_idf_list

#Put them into feature vector and store in
#test_case_feature_list
#----------------------------------------------------------------------------------------------
test_case_feature_list = testcase_stat.feature_vector_quantify(
    tf_idf_list, full_stat_list)