SELECT c.stock_id, a.stock_name, a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time, (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id) AS grant, (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND (status = "20" OR status = "30")) AS receive, (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND status = "30") AS writeOff FROM wx_coupon a LEFT JOIN baishiof_company b ON a.company_id = b.company_id LEFT JOIN user_coupon c ON a.id = c.activity_id GROUP BY c.stock_id, a.stock_name, a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time;以上代码出现了You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near 'grant , ( SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND (status ' at line 1这个错误，修复他

SELECT c.stock_id, a.stock_name, a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time, (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id) AS total_grant, (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND (status = "20" OR status = "30")) AS receive, (SELECT COUNT(1) FROM user_coupon WHERE activity_id = a.id AND status = "30") AS writeOff FROM wx_coupon a LEFT JOIN baishiof_company b ON a.company_id = b.company_id LEFT JOIN user_coupon c ON a.id = c.activity_id GROUP BY c.stock_id, a.stock_name, a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time;以上代码存在这个问题Expression #8 of SELECT list is not in GROUP BY clause and contains nonaggregated column 'baishiof.a.id' which is not functionally dependent on columns in GROUP BY clause; this is incompatible with sql_mode=only_full_group_by修复他

c.stock_id, a.stock_name, a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time, a.id; 在上面的修复中，将 a.id 添加到 GROUP BY 子句中。这样可以确保每个活动的 id 在...

select c.stock_id,a.stock_name,a.coupon_amount, a.transaction_minimum, b.company_name, a.start_time, a.end_time, (select count(1) from user_coupon where activity_id = a.id) as grant,(select count(1) from user_coupon where activity_id = a.id and (status = "20" or status = "30")) as receive,(select count(1) from user_coupon where activity_id = a.id and status = "30") as writeOff from wx_coupon a left join baishiof_company b on a.company_id = b.company_id left join user_coupon c on a.id = c.activity_id group by c.stock_id

- a.transaction_minimum: 交易最低额 - b.company_name: 公司名称 - a.start_time: 活动开始时间 - a.end_time: 活动结束时间 - (select count(1) from user_coupon where activity_id = a.id) as grant: 发放的...

select a.*, b.name activityName, c.name productName, c.member_max memberMax, d.status as complete, group_concat(if(e.face_value is null, "", e.face_value) separator "\n") as rewardAmount, group_concat(if(e.coupon_code is null, "", e.coupon_code ) separator "\n") as couponCode , group_concat(if(e.coupon_id is null, "", e.coupon_id) separator "\n") as caId from marketing_group_tool_group_member a left join marketing_group_tool_group_info d on a.group_id = d.id left join marketing_group_tool_activity b on a.activity_id = b.activity_id left join marketing_group_tool_product_base c on a.product_id = c.product_id left join marketing_group_tool_send_coupon_record e on (a.group_id = e.group_id and a.card_no = e.card_no) left join wx_recommend_organization organization on b.organization_id = organization.id where ((organization.tree_id between 2002000000000000 and 2002999999999999) or (organization.tree_id between 1000000000000000 and 1999999999999999) or (organization.tree_id between 2000000000000000 and 2999999999999999) or (organization.tree_id between 3000000000000000 and 3999999999999999) or (organization.tree_id between 4000000000000000 and 4999999999999999) or (organization.tree_id between 6000000000000000 and 6999999999999999) or (organization.tree_id between 5000000000000000 and 5999999999999999) or (organization.tree_id between 10000000000000000 and 10999999999999999) or (organization.tree_id between 8000000000000000 and 8999999999999999) or (organization.tree_id between 9000000000000000 and 9999999999999999) or (organization.tree_id between 11000000000000000 and 11999999999999999) or (organization.tree_id between 12000000000000000 and 12999999999999999) or (organization.tree_id between 13000000000000000 and 13999999999999999) or (organization.tree_id between 14000000000000000 and 14999999999999999) or (organization.tree_id between 15000000000000000 and 15999999999999999) or (organization.tree_id between 16000000000000000 and 16999999999999999) or (organization.tree_id between 17000000000000000 and 17999999999999999) ) and 1 = 1 group by a.id, a.activity_id , a.group_id , a.product_id , a.activity_referral_code, a.product_referral_code , a.openid , a.unionid , a.nickname , a.head_img , a.mobile , a.is_sub_buy , a.is_sub_progress , a.is_sub_success , a.sort , a.card_no , a.create_time , a.is_received_notice , a.is_received_progress , a.is_received_success , b.name, c.name, c.member_max , d.status order by a.id desc limit 0,20;

2. 避免使用 select *，只选择需要的字段，可以减少数据量和网络传输开销。 3. 尽量避免使用 group_concat，这会导致 MySQL 在内部生成临时表，会消耗大量的内存和 CPU 时间，可以考虑在应用层进行拼接。 4. ...

SELECT sum(t.pay_amount)+sum(t.promotion_amount)+SUM(t.author_coupon_subsidy)+SUM(t.actual_zt_pay_promotion)+SUM(t.actual_zr_pay_promotion)+SUM(t.refund_amount)+SUM(t.jylp_wp_amount)+SUM(t.post_amount)+SUM(t.promotion_amount_yf) as 'b_amount',\n" + "SUM(t.platform_service_fee)+SUM(t.commission)+SUM(t.channel_fee)+SUM(t.colonel_service_fee)+SUM(t.channel_promotion_fee)+SUM(t.other_sharing_amount)+SUM(t.yfx_amount)+SUM(t.jylp_yp_amount) as 's_amount'\n" + "from dy_settlement_push_input t where t.deleted = '0'

这是一条 SQL 查询语句，目的是查询 dy_settlement_push_input 表中满足条件（deleted = '0'）的记录中，各种金额字段的总和。具体来说，该语句计算了以下...最终会返回两个金额总和，分别是 b_amount 和 s_amount。

第一个SQL： SELECT orders.id,orders.user_id,orders.cityarea_id,orders.batchcode,orders.status, orders.pay_status,orders.real_pay,orders.total,orders.money,orders.pay_type, orders.premium,orders.createtime,orders.paytime,orders.confirmtime, orders.is_evaluate,orders.pay_method,orders.exp_user_id, orders.return_score, orders.is_change,orders.reward_money,orders.isvalid,orders.after_sale_status,orders.remark, orders.use_coupon_detail,orders.block_chain_price, users.name,users.weixin_name,users.weixin_fromuser, users.phone,wcoe.diy_area_name from wsy_o2o.weixin_cityarea_orders orders left join wsy_o2o.weixin_cityarea_supply supply on orders.cityarea_id = supply.id left join wsy_o2o.weixin_cityarea_payonline_orders wcco on orders.batchcode=wcco.batchcode left join wsy_user.weixin_users users on users.id = orders.user_id LEFT JOIN wsy_o2o.weixin_cityarea_orders_extend wcoe ON orders.batchcode = wcoe.batchcode WHERE orders.types=3 and orders.customer_id = 41 AND orders.isvalid=true GROUP BY orders.batchcode ORDER BY orders.id DESC limit 0,20; 第二个SQL： SELECT orders.id,orders.user_id,orders.cityarea_id,orders.batchcode,orders.status, orders.pay_status,orders.real_pay,orders.total,orders.money,orders.pay_type, orders.premium,orders.createtime,orders.paytime,orders.confirmtime, orders.is_evaluate,orders.pay_method,orders.exp_user_id, orders.return_score, orders.is_change,orders.reward_money,orders.isvalid,orders.after_sale_status,orders.remark, orders.use_coupon_detail,orders.block_chain_price, users.name,users.weixin_name,users.weixin_fromuser, users.phone,wcoe.diy_area_name ,writes.ActivityStatus,writes.NewMoney from wsy_o2o.weixin_cityarea_orders orders left join wsy_o2o.weixin_cityarea_supply supply on orders.cityarea_id = supply.id left join wsy_o2o.weixin_cityarea_payonline_orders wcco on orders.batchcode=wcco.batchcode left join wsy_user.weixin_users users on users.id = orders.user_id LEFT JOIN wsy_o2o.weixin_cityarea_orders_extend wcoe ON orders.batchcode = wcoe.batchcode LEFT JOIN wsy_dream.ShopWrite writes on orders.batchcode = writes.Batchcode WHERE orders.types=3 and orders.customer_id = 41 AND orders.isvalid=true GROUP BY orders.batchcode ORDER BY orders.id DESC limit 0,20; 为什么查询结果从0.7秒变成了3.7秒？

查询结果从0.7秒变成3.7秒可能是由于以下原因导致的： 1. SQL语句中的表连接（JOIN）操作过多：第二个SQL语句相较于第一个SQL语句多了一个表连接，即LEFT JOIN wsy_dream.ShopWrite writes on orders.batchcode = ...

INSERT INTO dy_check_statistics (ID, data_date, statistics_type, order_type, province_name, pay_amount, post_amount, promotion_amount, author_coupon_subsidy, actual_zt_pay_promotion, actual_zr_pay_promotion, refund_amount, platform_service_fee, commission, channel_fee, colonel_service_fee, channel_promotion_fee, other_sharing_amount, packing_amount, yfx_amount, promotion_amount_yf, jylp_yp_amount, jylp_wp_amount, txje, create_time, creator_name, update_time, updater_name, deleted, remark) select #{id}, #{date}, '1', NULL, NULL, IFNULL(sum(a.pay_amount),0), IFNULL(sum(a.post_amount),0), IFNULL(sum(a.promotion_amount),0), IFNULL(sum(a.author_coupon_subsidy),0), IFNULL(sum(a.actual_zt_pay_promotion),0), IFNULL(sum(a.actual_zr_pay_promotion),0), IFNULL(sum(a.refund_amount),0), IFNULL(sum(a.platform_service_fee),0), IFNULL(sum(a.commission),0), IFNULL(sum(a.channel_fee),0), IFNULL(sum(a.colonel_service_fee),0), IFNULL(sum(a.channel_promotion_fee),0), IFNULL(sum(a.other_sharing_amount),0), IFNULL(sum(a.packing_amount),0), IFNULL(sum(a.yfx_amount),0), IFNULL(sum(a.promotion_amount_yf),0), IFNULL(sum(a.jylp_yp_amount),0), IFNULL(sum(a.jylp_wp_amount),0), #{txje}, now(), 'system', now(), 'system', 0, NULL from ${fromTable} a

3. select #{id}, #{date}, '1', NULL, NULL, IFNULL(sum(a.pay_amount),0), IFNULL(sum(a.post_amount),0), IFNULL(sum(a.promotion_amount),0), IFNULL(sum(a.author_coupon_subsidy),0), IFNULL(sum(a.actual_zt...

is_wx = self.is_login(driver) if is_wx == 1: Element_UI.element_css_selector_click(driver, '[class="anticon anticon-close-circle"]') if self.is_coupon(driver) == 2: Element_UI.element_class_name_click(driver, 'ant-modal-close') else: pass else: if self.is_coupon(driver) == 2: Element_UI.element_class_name_click(driver, 'ant-modal-close') else: pass return True 翻译这段代码

这段代码是一个Python函数，实现的功能是在网页上点击一些... ... 如果没有登录，则直接判断是否有优惠券弹窗出现，如果有，则通过class name找到并点击一个关闭按钮，否则不做处理。最后，函数返回True表示执行成功。

优化下发代码 def init(self, driver): self.driver = driver self.wait = WebDriverWait(self.driver, 10) try: # 选择门店按钮 self.select_store_button = self.wait.until( EC.visibility_of_element_located((By.XPATH, '元素的xpath')) ) # 店名搜索框 self.select_store_input = self.wait.until( By.CSS_SELECTOR, 'div.index-module_account-select-search-wrapper__pWNeA input.life-core-input') # 始终选择搜索后的第一个店 self.store_button = self.wait.until(By.CSS_SELECTOR, ".index-module_account-select-item-pctextG0o02:first-child") # 券码输入框 self.coupon_input = self.wait.until(By.XPATH, '//input[@placeholder="请输入12-15位数字券码"]') # 验证按钮 self.coupon_button = self.wait.until( By.XPATH, '//div[@class="src-pages-HomeV2-components-VerificationV2-index-module__submitBtn--phChf--212e2"]') except TimeoutException: print('元素在页面中不可见')

self.select_store_input = self.find_element(By.CSS_SELECTOR, 'div.index-module_account-select-search-wrapper__pWNeA input.life-core-input') self.store_button = self.find_element(By.CSS_SELECTOR, "....

帮我解析一下这个java错误，Caused by: org.h2.jdbc.JdbcSQLSyntaxErrorException: Syntax error in SQL statement "SELECT C.PERIOD_NO, C.BILL_MONTH, C.LOCAL_AIR_CODE, C.INT_DOM_INDICATOR, 'GLOBAL' AS CHECK_CODE, CASE WHEN COUPON_COUNT_GLOBAL = COUPON_COUNT_REPORT AND TAX_AMT_GLOBAL = TAX_AMT_REPORT AND ISC_AMT_GLOBAL = ISC_AMT_REPORT AND UATP_AMT_GLOBAL = UATP_AMT_REPORT AND GROSS_AMT_GLOBAL = GROSS_AMT_REPORT THEN 'S' ELSE 'F' END AS CHECK_RESULT_IND, TAX_AMT_GLOBAL AS TAX_AMT_ACTUAL, TAX_AMT_REPORT AS TAX_AMT_EXPECTED, ISC_AMT_GLOBAL AS ISC_AMT_ACTUAL, ISC_AMT_REPORT AS ISC_AMT_EXPECTED, UATP_AMT_GLOBAL AS UATP_AMT_ACTUAL, UATP_AMT_REPORT AS UATP_AMT_EXPECTED, GROSS_AMT_GLOBAL AS GROSS_AMT_ACTUAL, GROSS_AMT_REPORT AS GROSS_AMT_EXPECTED, COUPON_COUNT_GLOBAL AS COUPON_COUNT_ACTUAL, COUPON_COUNT_REPORT AS COUPON_COUNT_EXPECTED FROM ( ( SELECT BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR, SUM(COUPON_COUNT) AS COUPON_COUNT_GLOBAL, CASE WHEN SUM(GROSS_AMT_BILLING) IS NULL THEN 0 ELSE SUM(GROSS_AMT_BILLING) END AS GROSS_AMT_GLOBAL, CASE WHEN SUM(BILL_TAX_BILLING) IS NULL THEN 0 ELSE SUM(BILL_TAX_BILLING) END AS TAX_AMT_GLOBAL, CASE WHEN SUM(ISC_AMT_BILLING) IS NULL THEN 0 ELSE SUM(ISC_AMT_BILLING) END AS ISC_AMT_GLOBAL, CASE WHEN SUM(UATP_AMT_BILLING) IS NULL THEN 0 ELSE SUM(UATP_AMT_BILLING) END AS UATP_AMT_GLOBAL FROM OWB_GLOBAL_REPORT WHERE REPORT_TYPE = 'R' AND DELETE_IND IS NULL AND PERIOD_NO = ? AND BILL_MONTH = ? AND INT_DOM_INDICATOR = ? AND LOCAL_AIR_CODE = ? GROUP BY BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR) C[*] INNER JOIN ( SELECT BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR, SUM(COUPON_COUNT) AS COUPON_COUNT_REPORT, CASE WHEN SUM(GROSS_AMT_BILLING) IS NULL THEN 0 ELSE SUM(GROSS_AMT_BILLING) END AS GROSS_AMT_REPORT, CASE WHEN SUM(BILL_TAX_BILLING) IS NULL THEN 0 ELSE SUM(BILL_TAX_BILLING) END AS TAX_AMT_REPORT, CASE WHEN SUM(ISC_AMT_BILLING) IS NULL THEN 0 ELSE SUM(ISC_AMT_BILLING) END AS ISC_AMT_REPORT, CASE WHEN SUM(UATP_AMT_BILLING) IS NULL THEN 0 ELSE SUM(UATP_AMT_BILLING) END AS UATP_AMT_REPORT FROM OWB_REPORT WHERE ADJ_MONTH IS NULL AND PERIOD_NO = ? AND BILL_MONTH = ? AND INT_DOM_INDICATOR = ? AND LOCAL_AIR_CODE = ? GROUP BY BILL_MONTH, PERIOD_NO, LOCAL_AIR_CODE, INT_DOM_INDICATOR) R ON C.BILL_MONTH = R.BILL_MONTH AND C.PERIOD_NO = R.PERIOD_NO AND C.LOCAL_AIR_CODE = R.LOCAL_AIR_CODE AND C.INT_DOM_INDICATOR = R.INT_DOM_INDICATOR )"; expected "UNION, EXCEPT, MINUS, INTERSECT, ORDER, OFFSET, FETCH, LIMIT, SAMPLE_SIZE, FOR, )";

这个错误是由于Java程序中的SQL语句存在语法错误导致的。根据错误信息，语法错误出现在SQL查询语句的最后部分。错误提示指出在预期的位置上应该是"UNION, EXCEPT, MINUS, INTERSECT, ORDER, OFFSET, FETCH, LIMIT, ...

#如果用户领取特定优惠券2次以上，那么提取出第一次和最后一次领取的时间 t2=dataset3[['user_id','coupon_id','date_received']] t2.date_received=t2.date_received.astype('str') t2=t2.groupby(['user_id','coupon_id'])['date_received'].agg(lambda x:':'.join(x)).reset_index() t2['receive_number']=t2.date_received.apply(lambda s:len(s.split(':'))) t2=t2[t2.receive_number>1] t2['max_date_received']=t2.date_received.apply(lambda s:max([int(d) for d in s.split(':')])) t2['min_date_received']=t2.date_received.apply(lambda s:min([int(d) for d in s.split(':')])) t2=t2[['user_id','coupon_id','max_date_received','min_date_received']] 详细解释这段代码

1. 首先，代码创建一个名为t2的新数据集，并将原始数据集中的'user_id'、'coupon_id'和'date_received'列加入其中。 2. 将't2'数据集中的日期格式转换为字符串类型。 3. 将't2'数据集按照'user_id'和'coupon_id'...

Traceback (most recent call last): File "d:\Users\lenovo\anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 3629, in get_loc return self._engine.get_loc(casted_key) File "pandas\_libs\index.pyx", line 136, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\index.pyx", line 163, in pandas._libs.index.IndexEngine.get_loc File "pandas\_libs\hashtable_class_helper.pxi", line 5198, in pandas._libs.hashtable.PyObjectHashTable.get_item File "pandas\_libs\hashtable_class_helper.pxi", line 5206, in pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: ('User_id', 'Coupon_id', 'max_date_received', 'min_date_received') The above exception was the direct cause of the following exception: Traceback (most recent call last): File "D:\python相关2\任务二.py", line 251, in <module> train = get_dataset(train_history_field, train_middle_field, train_label_field) File "D:\python相关2\任务二.py", line 147, in get_dataset user_feat = get_user_feat(label_field) # 用户特征 File "D:\python相关2\任务二.py", line 69, in get_user_feat t2=t2['User_id','Coupon_id','max_date_received','min_date_received'] File "d:\Users\lenovo\anaconda3\lib\site-packages\pandas\core\frame.py", line 3505, in getitem indexer = self.columns.get_loc(key) File "d:\Users\lenovo\anaconda3\lib\site-packages\pandas\core\indexes\base.py", line 3631, in get_loc raise KeyError(key) from err KeyError: ('User_id', 'Coupon_id', 'max_date_received', 'min_date_received')

这个错误可能是因为在调用 t2['User_id','Coupon_id','max_date_received','min_date_received'] 时，需要将 key 用中括号括起来，即 t2[['User_id','Coupon_id','max_date_received','min_date_received']]。

$(function(){ $(".head-title span").click(function(){ history.go(-1); }); $(".tab_coupon div").click(function(){ $(".tab_coupon div").removeClass("active"); $(this).addClass("active"); var type = $(this).data("type"); $(".list_coupon div").each(function(n){ $(this).hide(); if(n + 1 == type) $(this).show(); }); });

这是一段jQuery代码，用于实现交互功能。代码中包含两个事件处理函数： 1. 当".head-title span"元素被点击时，会执行一个匿名函数，该函数调用了history.go(-1)方法，用于返回上一页。 2. 当".tab_coupon div...

#预测函数 def get_predict(datas=datasets_yc,model=model,features=['Discount_rate','Distance'],outfiles='D:/a.python/a.python算法/1期末/数据挖掘实战案例_O2O优惠劵使用预测/temp/result01.csv'): data_yc = datas[features] pre_yc = model.predict_proba(data_yc)[:,1] result = datas[['User_id','Coupon_id','Date_received']] result['probability'] = pre_yc #保存为提交所用的csv文档 result.to_csv(outfiles,index=None,header=None)

这是一个使用指定模型对指定数据集进行预测的函数，其中： - 参数 datas 是一个DataFrame，包含待...- 将预测结果与原数据集中的用户ID、优惠券ID和领取日期合并为一个新的DataFrame，并将预测结果保存为CSV文件。

# 特征01归一化处理 ProcessDataSet1 = preprocess(dataset1, feature1, True) ProcessDataSet1_x = ProcessDataSet1.drop( ['user_id', 'label', 'coupon_id'], axis=1) for i in ProcessDataSet1_x.columns: ProcessDataSet1_x[i] = MinMaxScaler(copy=True, feature_range=(0, 1)).fit_transform(ProcessDataSet1_x[i].values.reshape(-1, 1)) ProcessDataSet1_norm = pd.concat([ProcessDataSet1['user_id'], ProcessDataSet1['label'], ProcessDataSet1['coupon_id'], ProcessDataSet1_x], axis=1) ProcessDataSet1_norm.to_csv(os.path.join(DataPath, 'ProcessDataSet1_norm.csv'), index=None)将上述代码改写，功能不变

ProcessDataSet1_x = ProcessDataSet1.drop(['user_id', 'label', 'coupon_id'], axis=1) scaler = MinMaxScaler(feature_range=(0, 1)) ProcessDataSet1_x = pd.DataFrame(scaler.fit_transform(ProcessDataSet1_x)...

if (requestParams.getCouponId()!=null && totalFee>=10000){ CouponVo couponVo = couponClient.getById(requestParams.getCouponId(), userId); if (couponVo==null){ throw new HmallException("用户劵不存在或已失效"); } if (couponVo.getRuleType()==CST.COUPON_RULE_TYPE_DEDUCE){ order.setTotalFee(totalFee-couponVo.getAmount()); }else if (couponVo.getRuleType()==CST.COUPON_RULE_TYPE_DISCOUNT){ order.setTotalFee(calc(totalFee,couponVo.getAmount())); } }

在这段代码中，你首先判断了请求参数中的优惠券ID是否不为空，并且订单的总费用是否大于等于10000。如果满足这两个条件，就根据优惠券的规则对订单的总费用进行处理。然而，你需要注意一些潜在的问题。在Java中，...

def model_xgb(train, test): """xgb模型 Args: Returns: """ # xgb参数 params = {'booster': 'gbtree', 'objective': 'binary:logistic', 'eval_metric': 'auc', 'silent': 1, 'eta': 0.01, 'max_depth': 5, 'min_child_weight': 1, 'gamma': 0, 'lambda': 1, 'colsample_bylevel': 0.7, 'colsample_bytree': 0.7, 'subsample': 0.9, 'scale_pos_weight': 1} # 数据集 dtrain = xgb.DMatrix(train.drop(['User_id', 'Coupon_id', 'Date_received', 'label'], axis=1), label=train['label']) dtest = xgb.DMatrix(test.drop(['User_id', 'Coupon_id', 'Date_received'], axis=1)) # 训练 watchlist = [(dtrain, 'train')] model = xgb.train(params, dtrain, num_boost_round=500, evals=watchlist) # 预测 predict = model.predict(dtest) # 处理结果 predict = pd.DataFrame(predict, columns=['prob']) result = pd.concat([test[['User_id', 'Coupon_id', 'Date_received']], predict], axis=1) # 特征重要性 feat_importance = pd.DataFrame(columns=['feature_name', 'importance']) feat_importance['feature_name'] = model.get_score().keys() feat_importance['importance'] = model.get_score().values() feat_importance.sort_values(['importance'], ascending=False, inplace=True) # 返回 return result, feat_importance解释一下

将预测结果和测试数据集中的 User_id、Coupon_id、Date_received 列进行合并，得到最终的预测结果。 5. 使用 XGBoost 的 get_score 函数获取特征重要性，并将其保存为一个 DataFrame 对象，包括每个特征的...

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