{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "c6e41d140bb8f818", "metadata": { "collapsed": false, "jupyter": { "outputs_hidden": false } }, "outputs": [], "source": [ "# 一、选择特征" ] }, { "cell_type": "code", "execution_count": 1, "id": "063d5686-3a6b-4879-ba01-32d6674528d8", "metadata": { "ExecuteTime": { "end_time": "2024-08-08T06:42:34.495238Z", "start_time": "2024-08-08T06:42:34.280113Z" }, "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
\n", " | \n", " | 地区生产总值(亿元) | \n", "人均地区生产总值(按常住人口)(万元) | \n", "人均地区生产总值(按户籍人口)(万元) | \n", "固定资产投资(亿元) | \n", "年末户籍人口(万人) | \n", "年末常住人口(万人) | \n", "人口密度(人/平方千米) | \n", "城镇化率(%)城镇人口/总人口 | \n", "行政区域土地面积(平方千米) | \n", "年末耕地总资源 | \n", "... | \n", "社会消费品零售总额(亿元) | \n", "当年实际使用外资金额(亿美元) | \n", "地方一般公共预算收入(亿元) | \n", "地方一般公共预算支出(亿元) | \n", "教育支出(亿元) | \n", "政策影响 | \n", "住宅用地(万元/㎡) | \n", "工业用地(万元/㎡) | \n", "商服用地(万元/㎡) | \n", "其他用地(万元/㎡) | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
城市 | \n", "年度 | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
杭州西湖 | \n", "2023 | \n", "2087.40 | \n", "17.8600 | \n", "25.580882 | \n", "555.2 | \n", "81.6 | \n", "117.1 | \n", "3749.000000 | \n", "97.5 | \n", "312.43 | \n", "2123.0 | \n", "... | \n", "906.3 | \n", "4.00 | \n", "233.80 | \n", "169.30 | \n", "57.40 | \n", "0.5 | \n", "1.53 | \n", "0.14 | \n", "0.70 | \n", "0.00 | \n", "
2022 | \n", "1970.10 | \n", "17.2438 | \n", "24.601300 | \n", "484.0 | \n", "80.5 | \n", "116.7 | \n", "3735.236693 | \n", "97.4 | \n", "312.43 | \n", "2123.0 | \n", "... | \n", "845.7 | \n", "7.01 | \n", "233.50 | \n", "149.80 | \n", "35.70 | \n", "0.5 | \n", "3.15 | \n", "0.13 | \n", "1.69 | \n", "0.01 | \n", "|
2021 | \n", "1904.20 | \n", "17.2405 | \n", "24.258200 | \n", "472.1 | \n", "79.6 | \n", "111.8 | \n", "3578.401562 | \n", "97.1 | \n", "312.43 | \n", "2112.0 | \n", "... | \n", "787.6 | \n", "8.30 | \n", "175.70 | \n", "127.00 | \n", "45.40 | \n", "0.5 | \n", "2.98 | \n", "0.12 | \n", "1.44 | \n", "0.02 | \n", "|
2020 | \n", "1587.60 | \n", "14.7819 | \n", "20.512800 | \n", "468.9 | \n", "77.4 | \n", "109.1 | \n", "3603.000000 | \n", "97.0 | \n", "309.00 | \n", "2133.0 | \n", "... | \n", "689.7 | \n", "10.10 | \n", "162.00 | \n", "190.60 | \n", "27.70 | \n", "1.0 | \n", "2.54 | \n", "0.11 | \n", "1.52 | \n", "0.02 | \n", "|
2019 | \n", "1415.83 | \n", "16.0161 | \n", "19.272500 | \n", "457.6 | \n", "74.9 | \n", "90.8 | \n", "3031.000000 | \n", "96.9 | \n", "309.00 | \n", "2164.0 | \n", "... | \n", "711.7 | \n", "7.02 | \n", "150.64 | \n", "93.01 | \n", "20.36 | \n", "1.0 | \n", "0.71 | \n", "0.30 | \n", "1.84 | \n", "0.01 | \n", "
5 rows × 27 columns
\n", "XGBRegressor(base_score=None, booster=None, callbacks=None,\n", " colsample_bylevel=None, colsample_bynode=None,\n", " colsample_bytree=None, device=None, early_stopping_rounds=None,\n", " enable_categorical=False, eval_metric=None, feature_types=None,\n", " gamma=None, grow_policy=None, importance_type=None,\n", " interaction_constraints=None, learning_rate=None, max_bin=None,\n", " max_cat_threshold=None, max_cat_to_onehot=None,\n", " max_delta_step=None, max_depth=None, max_leaves=None,\n", " min_child_weight=None, missing=nan, monotone_constraints=None,\n", " multi_strategy=None, n_estimators=None, n_jobs=None,\n", " num_parallel_tree=None, random_state=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
XGBRegressor(base_score=None, booster=None, callbacks=None,\n", " colsample_bylevel=None, colsample_bynode=None,\n", " colsample_bytree=None, device=None, early_stopping_rounds=None,\n", " enable_categorical=False, eval_metric=None, feature_types=None,\n", " gamma=None, grow_policy=None, importance_type=None,\n", " interaction_constraints=None, learning_rate=None, max_bin=None,\n", " max_cat_threshold=None, max_cat_to_onehot=None,\n", " max_delta_step=None, max_depth=None, max_leaves=None,\n", " min_child_weight=None, missing=nan, monotone_constraints=None,\n", " multi_strategy=None, n_estimators=None, n_jobs=None,\n", " num_parallel_tree=None, random_state=None, ...)
XGBRegressor(base_score=None, booster='gbtree', callbacks=None,\n", " colsample_bylevel=None, colsample_bynode=None,\n", " colsample_bytree=None, device=None, early_stopping_rounds=None,\n", " enable_categorical=False, eval_metric=None, feature_types=None,\n", " gamma=None, grow_policy=None, importance_type=None,\n", " interaction_constraints=None, learning_rate=0.01, max_bin=None,\n", " max_cat_threshold=None, max_cat_to_onehot=None,\n", " max_delta_step=None, max_depth=None, max_leaves=None,\n", " min_child_weight=None, missing=nan, monotone_constraints=None,\n", " multi_strategy=None, n_estimators=125, n_jobs=None,\n", " num_parallel_tree=None, random_state=None, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
XGBRegressor(base_score=None, booster='gbtree', callbacks=None,\n", " colsample_bylevel=None, colsample_bynode=None,\n", " colsample_bytree=None, device=None, early_stopping_rounds=None,\n", " enable_categorical=False, eval_metric=None, feature_types=None,\n", " gamma=None, grow_policy=None, importance_type=None,\n", " interaction_constraints=None, learning_rate=0.01, max_bin=None,\n", " max_cat_threshold=None, max_cat_to_onehot=None,\n", " max_delta_step=None, max_depth=None, max_leaves=None,\n", " min_child_weight=None, missing=nan, monotone_constraints=None,\n", " multi_strategy=None, n_estimators=125, n_jobs=None,\n", " num_parallel_tree=None, random_state=None, ...)