我正在尝试验证我的逻辑回归模型

Question

X=train.drop('Loan_Status', 1)
y=train.Loan_Status


X=pd.get_dummies(X)
train=pd.get_dummies(train)
test=pd.get_dummies(test)

from sklearn.model_selection import train_test_split
X_train, X_cv, y_train, y_cv=train_test_split(X,y, test_size=0.3)

from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score

model= LogisticRegression()
model.fit=(X_train, y_train)

LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True, 
                   intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1, 
                   penalty='l2', random_state=1, solver='liblinear', tol=0.0001, 
                   verbose=0, warm_start=False)

pred_cv=model.predict(X_cv)

但是我收到了这个错误：

“NotFittedError：此 LogisticRegression 实例尚未拟合。在使用此估算器之前，请使用适当的参数调用 'fit'。”

Answer 1

我认为这只是一个语法问题：

model.fit=(X_train, y_train)

应该是

model.fit(X_train, y_train)