本文整理汇总了Python中sklearn.svm.SVC.degree方法的典型用法代码示例。如果您正苦于以下问题：Python SVC.degree方法的具体用法？Python SVC.degree怎么用？Python SVC.degree使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.svm.SVC的用法示例。
在下文中一共展示了SVC.degree方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: trainauc
# 需要导入模块: from sklearn.svm import SVC [as 别名]
# 或者: from sklearn.svm.SVC import degree [as 别名]
def trainauc (self, train, trainlabel, seed, Cmin, Cmax, numC, rmin, rmax, numr, degree=3, method = 'roc_auc', rad_stat =2):
C_range=np.logspace(Cmin, Cmax, num=numC, base=2,endpoint= True)
gamma_range=np.logspace(rmin, rmax, num=numr, base=2,endpoint= True)
svc = SVC(kernel=seed)
# mean_score=[]
df_C_gamma= DataFrame({'gamma_range':gamma_range})
# df_this = DataFrame({'gamma_range':gamma_range})
count = 0
for C in C_range:
score_C=[]
# score_C_this = []
count=count+1
for gamma in gamma_range:
svc.C = C
svc.gamma = gamma
svc.degree = degree
svc.random_state = rad_stat
this_scores = cross_val_score(svc, train, trainlabel, scoring=method, cv=10, n_jobs=-1 \
)
score_C.append(np.mean(this_scores))
#score_C_this.append(np.mean(this_scores))
print (np.mean(score_C) )
print ("%r cycle finished, %r left" %(count, numC-count))
df_C_gamma[C]= score_C
#df_this[C] = score_C_this
return df_C_gamma 示例2: trainSVC
# 需要导入模块: from sklearn.svm import SVC [as 别名]
# 或者: from sklearn.svm.SVC import degree [as 别名]
def trainSVC (self, train, trainlabel, seed, Cmin, Cmax, numC, rmin, rmax, numr, degree=3):
C_range=np.logspace(Cmin, Cmax, num=numC, base=2,endpoint= True)
gamma_range=np.logspace(rmin, rmax, num=numr, base=2,endpoint= True)
svc = SVC(kernel=seed)
# mean_score=[]
df_C_gamma= DataFrame({'gamma_range':gamma_range})
# df_this = DataFrame({'gamma_range':gamma_range})
count = 0
for C in C_range:
score_C=[]
# score_C_this = []
count=count+1
for gamma in gamma_range:
training_manCV.secret_cm=[]
training_manCV.secret_score=[]
svc.C = C
svc.gamma = gamma
svc.degree = degree
this_scores = cross_val_score(svc, train, trainlabel, scoring=training_manCV().metric_scores, cv=10, n_jobs=-1)
df_raw0 = DataFrame({'cm':training_manCV.secret_cm})
score_C.append(np.mean(df_raw0['cm'].tail(10)))
#score_C_this.append(np.mean(this_scores))
print (np.mean(this_scores) )
print ("%r cycle finished, %r left" %(count, numC-count))
df_C_gamma[C]= score_C
#df_this[C] = score_C_this
return df_C_gamma