使用Python进行logistic regression_python中调用logisticregression函数需要加载哪个包

# Step 1: Import packages, functions, and classes
import numpy as np
import seaborn as sns
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import classification_report, confusion_matrix
 
sns.set_theme()# 设置风格
%config InlineBackend.figure_format = 'retina' # 让图片更清晰
 
# Step 2: Get data
x = np.arange(10).reshape(-1, 1)
y = np.array([0, 1, 0, 0, 1, 1, 1, 1, 1, 1])
 
# Step 3: Create a model and train it
model = LogisticRegression()
model.fit(x, y)
 
# Step 4: Evaluate the model
p_pred = model.predict_proba(x)
y_pred = model.predict(x)
score_ = model.score(x, y)
conf_m = confusion_matrix(y, y_pred)
report = classification_report(y, y_pred)
 
print('report:', report, sep='\n')