地球资源数据云——数据资源详情
该数据集《Wheat Variety Classification》主要用于多分类任务,数据形态以表格为主。 题目说明:Classify the variety of wheat kernel based on physical attributes 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:wheat.csv。 Data Set Information: The dataset comprised wheat kernels belonging to three different varieties of wheat: Kama, Rosa and Canadian, 70 elements each. The data set can be used for the tasks of classification and cluster analysis.All of these parameters were real - valued continuous Attribute Information: To construct the data, seven geometric parameters of wheat kernels were measured: 1. area A,

该数据集《Wheat Variety Classification》主要用于多分类任务,数据形态以表格为主。 题目说明:Classify the variety of wheat kernel based on physical attributes
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:wheat.csv。
Data Set Information:
The dataset comprised wheat kernels belonging to three different varieties of wheat: Kama, Rosa and Canadian, 70 elements each. The data set can be used for the tasks of classification and cluster analysis.All of these parameters were real - valued continuous
Attribute Information:
To construct the data, seven geometric parameters of wheat kernels were measured:
1. area A,