def clf_vote(dataVolume,no_rand_rate=0):
data = createData.createData(dataVolume) # 星期(2) 天气(2) 时间(6) 行进方向(4) 离基站方向(6) 前一个BS(6)
x, y = data[:, :-1], data[:, -1]
if no_rand_rate != 0 :
for i in range(len(y)):
if y[i] % no_rand_rate == 0:
y[i] = random.randint(1, 6)
X_train, X_test, y_train, y_test = train_test_split(x , y, test_size = 0.5, random_state = 42)
svm_clf = Classifiers.svm_estimator(X_train,y_train)
RF_clf = Classifiers.RandomForest_best_estimator(X_train,y_train)
DT_clf = Classifiers.DecisionTree_best_estimator(X_train,y_train)
mlp_clf = Classifiers.MLPClassifier_estimator(X_train,y_train)
count = 0.0
time_start = time.time()
pre_svm = list(svm_clf.predict(X_test))
pre_RF = list(RF_clf.predict(X_test))
pre_DT = list(DT_clf.predict(X_test))
pre_MLP = list(mlp_clf.predict(X_test))
time_end = time.time()
time_pre = time_end - time_start
for i in range(len(pre_svm)):
vote_dict = {1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0}
vote_dict[pre_svm[i]] += 1
vote_dict[pre_RF[i]] += 1
vote_dict[pre_DT[i]] += 1
vote_dict[pre_MLP[i]] += 1
vote_result = max(vote_dict, key=vote_dict.get)
if vote_result == y_test[i]:
count +=1
acc = count / len(y_test)
return time_pre,acc
def dataVolume_runtime(dataVolume, no_rand_rate=2):
# data = cd.createData(dataVolume)
data = createData.createData(
dataVolume) #星期(2) 天气(2) 时间(6) 行进方向(4) 离基站方向(6) 前一个BS(6)
# data = data_normalized.createData(dataVolume)
x, y = data[:, :-1], data[:, -1]
for i in range(len(y)):
if y[i] % no_rand_rate == 0:
y[i] = random.randint(1, 6)
print('data set done!')
#DecisionTree:
bestTree = clf.DecisionTree_best_estimator(x, y)
DTScore = cross_val_score(bestTree, x, y)
#k-Neighbors:
k_best = clf.k_neighbors_best_estimator(x, y)
k_Neighbors_score = cross_val_score(k_best, x, y)
#randomforest:
rf_best = clf.RandomForest_best_estimator(x, y)
rf_score = cross_val_score(rf_best, x, y)
#svm:
svm_model = clf.svm_estimator(x, y)
svm_score = cross_val_score(svm_model, x, y)
#MLPClassifier
nn_best = clf.MLPClassifier_estimator(x, y)
nn_score = cross_val_score(nn_best, x, y, cv=6)
#vote
vote_time, vote_acc = vote.clf_vote(dataVolume * 2,
no_rand_rate=no_rand_rate)
# return DTScore,k_Neighbors_score,rf_score,svm_score,dttime,knntime,rftime,svmtime
return float(sum(DTScore)) / len(DTScore),float(sum(k_Neighbors_score)) / len(k_Neighbors_score),\
float(sum(rf_score)) / len(rf_score),float(sum(svm_score)) / len(svm_score), \
float(sum(nn_score)) / len(nn_score),vote_acc,vote_time
