def whole_evaluation(self):
e = Evaluation()
sql = "SELECT score1, score2, score3, score4, score5 From experiment_system_user Where system_type = 1"
self.cursor.execute(sql)
w2v_score = []
w2v_scores = []
scores_list = self.cursor.fetchall()
for score_list in scores_list:
w2v_score.append(score_list[0])
w2v_score.append(score_list[1])
w2v_score.append(score_list[2])
w2v_score.append(score_list[3])
w2v_score.append(score_list[4])
w2v_scores.append(w2v_score)
w2v_score = []
sql = "SELECT score1, score2, score3, score4, score5 From experiment_system_user Where system_type = 2"
self.cursor.execute(sql)
rstr_score = []
rstr_scores = []
scores_list = self.cursor.fetchall()
for score_list in scores_list:
rstr_score.append(score_list[0])
rstr_score.append(score_list[1])
rstr_score.append(score_list[2])
rstr_score.append(score_list[3])
rstr_score.append(score_list[4])
rstr_scores.append(rstr_score)
rstr_score = []
print("w2v_scores:" + str(w2v_scores))
print("length:" + str(len(w2v_scores)))
print("rstr_scores:" + str(rstr_scores))
print("length:" + str(len(rstr_scores)))
w2v_ndcg = e.average_ndcg(w2v_scores)
w2v_MAP = e.MAP(w2v_scores)
rstr_ndcg = e.average_ndcg(rstr_scores)
rstr_MAP = e.MAP(rstr_scores)
print("\nNDCG:")
print(w2v_ndcg)
print(rstr_ndcg)
plt.title("Evaluate System Performance NDCG@k")
plt.xlabel("Top K Recommendation")
plt.ylabel("NDCG@k")
plt.plot(range(1, 6), w2v_ndcg, "-v", color='y', label="W2V")
plt.plot(range(1, 6), rstr_ndcg, "-v", color='m', label="RSTR")
plt.legend(loc="best")
# save image
plt.savefig('image/System_NDCG.png')
plt.close()
print("\nMAP:")
print(w2v_MAP)
print(rstr_MAP)
plt.title("Evaluate System Performance MAP@k")
plt.xlabel("Top K Recommendation")
plt.ylabel("MAP@k")
plt.plot(range(1, 6), w2v_MAP, "-v", color='y', label="W2V")
plt.plot(range(1, 6), rstr_MAP, "-v", color='m', label="RSTR")
plt.legend(loc="best")
# save image
plt.savefig('image/System_MAP.png')
plt.close()
def calculate_score_and_show_result(self, w2v_150_socres, w2v_300_scores,
bert_768_scores):
e = Evaluation()
w2v_precision_150 = e.average_precision(w2v_150_socres, 2)
w2v_ndcg_150 = e.average_ndcg(w2v_150_socres)
w2v_precision_300 = e.average_precision(w2v_300_scores, 2)
w2v_ndcg_300 = e.average_ndcg(w2v_300_scores)
bert_precision_768 = e.average_precision(bert_768_scores, 2)
bert_ndcg_768 = e.average_ndcg(bert_768_scores)
print(w2v_precision_150)
print(w2v_ndcg_150)
print(w2v_precision_300)
print(w2v_ndcg_300)
print(bert_precision_768)
print(bert_ndcg_768)
plt.title("Semantic Prediction in Frequent Emotions and Events")
plt.xlabel(
"The number of predict semantic for each emotions or events")
plt.ylabel("Average Precision")
plt.plot(range(1, 11),
w2v_precision_150,
"-o",
color='r',
label="e2v-w2v-sg 150 dimension") # 畫出平均數值
plt.plot(range(1, 11),
w2v_precision_300,
"-o",
color='b',
label="e2v-w2v-sg 300 dimension") # 畫出平均數值
plt.plot(range(1, 11),
bert_precision_768,
"-o",
color='g',
label="e2v-bert 768 dimension") # 畫出平均數值
plt.legend(loc="best")
# save image
plt.savefig('image/precision.png')
plt.close()
plt.title("Semantic Prediction in Frequent Emotions and Events")
plt.xlabel(
"The number of predict semantic for each emotions or events")
plt.ylabel("Average NDCG")
plt.plot(range(1, 11),
w2v_ndcg_150,
"-o",
color='r',
label="e2v-w2v-sg 150 dimension") # 畫出平均數值
plt.plot(range(1, 11),
w2v_ndcg_300,
"-o",
color='b',
label="e2v-w2v-sg 300 dimension") # 畫出平均數值
plt.plot(range(1, 11),
bert_ndcg_768,
"-o",
color='g',
label="e2v-bert 768 dimension") # 畫出平均數值
plt.legend(loc="best")
# save image
plt.savefig('image/ndcg.png')
plt.close()
def individual_evaluation(self):
e = Evaluation()
sql = "SELECT article_id, score1, score2, score3, score4, score5 From experiment_system_user Where system_type = 2"
self.cursor.execute(sql)
e2v_score = []
e2v_kinship_scores = []
e2v_romantic_scores = []
e2v_friendship_scores = []
e2v_teacher_student_scores = []
e2v_business_scores = []
e2v_others_scores = []
scores_list = self.cursor.fetchall()
for score_list in scores_list:
sql = "SELECT relationship_type From articles Where id = " + str(
score_list[0])
self.cursor.execute(sql)
relationship_type = self.cursor.fetchone()
relationship_type = relationship_type[0]
print("article_id:" + str(score_list[0]) + " relationship_type:" +
str(relationship_type))
if relationship_type == '1':
e2v_score.append(score_list[1])
e2v_score.append(score_list[2])
e2v_score.append(score_list[3])
e2v_score.append(score_list[4])
e2v_score.append(score_list[5])
e2v_kinship_scores.append(e2v_score)
e2v_score = []
if relationship_type == '2':
e2v_score.append(score_list[1])
e2v_score.append(score_list[2])
e2v_score.append(score_list[3])
e2v_score.append(score_list[4])
e2v_score.append(score_list[5])
e2v_romantic_scores.append(e2v_score)
e2v_score = []
if relationship_type == '3':
e2v_score.append(score_list[1])
e2v_score.append(score_list[2])
e2v_score.append(score_list[3])
e2v_score.append(score_list[4])
e2v_score.append(score_list[5])
e2v_friendship_scores.append(e2v_score)
e2v_score = []
if relationship_type == '4':
e2v_score.append(score_list[1])
e2v_score.append(score_list[2])
e2v_score.append(score_list[3])
e2v_score.append(score_list[4])
e2v_score.append(score_list[5])
e2v_teacher_student_scores.append(e2v_score)
e2v_score = []
if relationship_type == '5':
e2v_score.append(score_list[1])
e2v_score.append(score_list[2])
e2v_score.append(score_list[3])
e2v_score.append(score_list[4])
e2v_score.append(score_list[5])
e2v_business_scores.append(e2v_score)
e2v_score = []
if relationship_type == '6':
e2v_score.append(score_list[1])
e2v_score.append(score_list[2])
e2v_score.append(score_list[3])
e2v_score.append(score_list[4])
e2v_score.append(score_list[5])
e2v_others_scores.append(e2v_score)
e2v_score = []
print("kinship:" + str(e2v_kinship_scores))
print("length:" + str(len(e2v_kinship_scores)))
print("remantic:" + str(e2v_romantic_scores))
print("length:" + str(len(e2v_romantic_scores)))
print("friendship:" + str(e2v_friendship_scores))
print("length:" + str(len(e2v_friendship_scores)))
print("teacher student:" + str(e2v_teacher_student_scores))
print("length:" + str(len(e2v_teacher_student_scores)))
print("business:" + str(e2v_business_scores))
print("length:" + str(len(e2v_business_scores)))
print("others:" + str(e2v_others_scores))
print("length:" + str(len(e2v_others_scores)))
e2v_kinship_ndcg = e.average_ndcg(e2v_kinship_scores)
e2v_romantic_ndcg = e.average_ndcg(e2v_romantic_scores)
e2v_friendship_ndcg = e.average_ndcg(e2v_friendship_scores)
e2v_teacher_student_ndcg = e.average_ndcg(e2v_teacher_student_scores)
e2v_business_ndcg = e.average_ndcg(e2v_business_scores)
e2v_others_ndcg = e.average_ndcg(e2v_others_scores)
e2v_kinship_MAP = e.MAP(e2v_kinship_scores)
e2v_romantic_MAP = e.MAP(e2v_romantic_scores)
e2v_friendship_MAP = e.MAP(e2v_friendship_scores)
e2v_teacher_student_MAP = e.MAP(e2v_teacher_student_scores)
e2v_business_MAP = e.MAP(e2v_business_scores)
e2v_others_MAP = e.MAP(e2v_others_scores)
plt.title("Evaluate Different Relationship Performance NDCG@k")
plt.xlabel("Top K Recommendation")
plt.ylabel("NDCG@k")
plt.plot(range(1, 6),
e2v_kinship_ndcg,
"-v",
color='y',
label="kinship")
plt.plot(range(1, 6),
e2v_romantic_ndcg,
"-v",
color='m',
label="romantic relationship")
plt.plot(range(1, 6),
e2v_friendship_ndcg,
"-v",
color='g',
label="friendship")
plt.plot(range(1, 6),
e2v_teacher_student_ndcg,
"-v",
color='b',
label="teacher student relationship")
plt.plot(range(1, 6),
e2v_business_ndcg,
"-v",
color='c',
label="business relationship")
plt.plot(range(1, 6), e2v_others_ndcg, "-v", color='k', label="others")
plt.legend(loc="best")
# save image
plt.savefig('image/Relationship_NDCG.png')
plt.close()
plt.title("Evaluate Different Relationship Performance MAP@k")
plt.xlabel("Top K Recommendation")
plt.ylabel("MAP@k")
plt.plot(range(1, 6),
e2v_kinship_MAP,
"-v",
color='y',
label="kinship")
plt.plot(range(1, 6),
e2v_romantic_MAP,
"-v",
color='m',
label="romantic relationship")
plt.plot(range(1, 6),
e2v_friendship_MAP,
"-v",
color='g',
label="friendship")
plt.plot(range(1, 6),
e2v_teacher_student_MAP,
"-v",
color='b',
label="teacher student relationship")
plt.plot(range(1, 6),
e2v_business_MAP,
"-v",
color='c',
label="business relationship")
plt.plot(range(1, 6), e2v_others_MAP, "-v", color='k', label="others")
plt.legend(loc="best")
# save image
plt.savefig('image/Relationship_MAP.png')
plt.close()
