fit() 缺少 1 个必需的位置参数：'self'

Question

我尝试将 SVC 放入 skikit-learn，但结果是 TypeError: fit() missing 1 required positional argument: 'self' in the line SVC.fit(X=Xtrain, y=ytrain)

from sklearn.svm import SVC
import seaborn as sns; sns.set()


from sklearn.datasets.samples_generator import make_circles
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_val_score


X, y = make_circles(100, factor=.2, noise=.2)
Xtrain, Xtest, ytrain, ytest = train_test_split(X,y,random_state=42)

svc = SVC(kernel = "poly")
SVC.fit(X=Xtrain, y=ytrain)
predictions = SVC.predict(ytest)

Answer 1

问题是您在此处创建模型 svc = SVC(kernel = "poly")，但您使用 non-instantiable 模型调用拟合。

您必须将对象更改为：

svc_model = SVC(kernel = "poly")
svc_model.fit(X=Xtrain, y=ytrain)
predictions = svc_model.predict(Xtest)

我建议你 Indique 测试大小，通常最好的做法是 30% 用于测试，70% 用于训练。所以你可以指出。

Xtrain, Xtest, ytrain, ytest = train_test_split(X,y,test_size=0.30, random_state=42)

fit() 缺少 1 个必需的位置参数：'self'

fit() missing 1 required positional argument: 'self'

svc

scikit-learn