从平均GLM模型绘制预测:计算时出错(预变量，数据，环境)：找不到对象'x3‘

import pandas as pd

# 假设df是你的数据框
print(df.columns)  # 查看所有列名

df['x3'] = 0  # 或者 df['x3'] = pd.NA

# 错误的引用示例
y_pred = model.predict(df[['x1', 'x2', 'x3错误的名字']])

# 正确的引用示例
y_pred = model.predict(df[['x1', 'x2', 'x3']])

# 假设之前有这样的操作
df = df.drop(['x3'], axis=1)  # 这会删除x3列

from sklearn.linear_model import PoissonRegressor
import pandas as pd

# 假设df是你的数据框，且已经包含了'x1', 'x2', 'x3'等特征
features = ['x1', 'x2', 'x3']

# 检查所需特征是否都在数据集中
missing_features = [feature for feature in features if feature not in df.columns]
if missing_features:
    raise ValueError(f"Missing features: {missing_features}")

# 训练模型
model = PoissonRegressor()
model.fit(df[features], df['target'])

# 进行预测
predictions = model.predict(df[features])