地球资源数据云——数据资源详情
该数据集《Car Classification Dataset》主要用于多分类任务,数据形态以表格为主,应用场景偏向交通/汽车。 题目说明:Can you evaluate which car is better? 任务类型:表格多分类。 建议流程:先做缺失值/异常值处理与特征编码,再比较逻辑回归、随机森林、XGBoost。 评估建议:使用分层切分或交叉验证,优先关注 F1、Recall、AUC 等分类指标。 可用文件:cars.csv。 SOURCE: LINK Derived from simple hierarchical decision model, this database may be useful for testing constructive induction and structure discovery methods. | Variable Name | Role | Type | Description | Units | Missing Values | | buying | Feature | Categorical | buying price | | no | | maint | Feature | Categorical | price of the maintenance | | no |

该数据集《Car Classification Dataset》主要用于多分类任务,数据形态以表格为主,应用场景偏向交通/汽车。 题目说明:Can you evaluate which car is better?
任务类型:表格多分类。
建议流程:先做缺失值/异常值处理与特征编码,再比较逻辑回归、随机森林、XGBoost。
评估建议:使用分层切分或交叉验证,优先关注 F1、Recall、AUC 等分类指标。
可用文件:cars.csv。
SOURCE: LINK
Derived from simple hierarchical decision model, this database may be useful for testing constructive induction and structure discovery methods.
| Variable Name | Role | Type | Description | Units | Missing Values |
| buying | Feature | Categorical | buying price | | no |
| maint | Feature | Categorical | price of the maintenance | | no |