实战四十一：机器学习特征因子筛选教程+回归预测实战 使用随机森林筛选特征，GradientBoosting预测数据

代码讲解请看：机器学习特征因子筛选教程+回归预测实战_哔哩哔哩_bilibili

项目结果：

完整代码：

from sklearn.tree import DecisionTreeClassifier
import pandas as pd
from sklearn.model_selection import train_test_split
from pathlib import Path
import numpy as np
from sklearn.pipeline import Pipeline
from sklearn.ensemble import GradientBoostingRegressor
# 导入自建包
import pumpflow_pp_rfct_2Jul22 as pp
from sklearn.ensemble import GradientBoostingRegressor
import pumpflow_pp_rfct_2Jul22 as pp
from sklearn.metrics import (
    mean_squared_error, mean_absolute_error,
    mean_absolute_percentage_error, median_absolute_error,
    r2_score, explained_variance_score)
local_base_dir = Path('')
p = local_b