地球资源数据云——数据资源详情
高等院校入学问答
该数据集《Q&A for Admission of Higher Education Institution》主要用于监督学习任务，数据形态以表格为主，应用场景偏向安全检测。 题目说明：Unlocking Insights for Higher Education Admissions Through Data Exploration 任务类型：表格监督学习。 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：未检测到标准 CSV，可优先查看目录中的索引或说明文件。 Dataset Question Answering for Admission of Higher Education Institution Description The data collection process commenced with web scraping of a selected higher education institution's website, collecting any data that relates to the admission topic of higher education institutions, during the period from July to September 2023. This resulted in a raw dataset primarily cantered around admission - related content. Subsequently, meticulous data cleaning and organization procedures were implemented to refine the dataset. The primary data, in its raw form before annotation into a question - and - answer format, was predominantly in the Indonesian language. Following this, a comprehensive annotation process was conducted to enrich the dataset with specific admission - related information, transforming it into secondary data. Both primary and secondary data predominantly remained in the Indonesian language.
摘要概览
该数据集《Q&A for Admission of Higher Education Institution》主要用于监督学习任务，数据形态以表格为主，应用场景偏向安全检测。 题目说明：Unlocking Insights for Higher Education Admissions Through Data Exploration
任务类型：表格监督学习。
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：未检测到标准 CSV，可优先查看目录中的索引或说明文件。
Dataset Question Answering for Admission of Higher Education Institution
Description
The data collection process commenced with web scraping of a selected higher education institution's website, collecting any data that relates to the admission topic of higher education institutions, during the period from July to September 2023. This resulted in a raw dataset primarily cantered around admission - related content.
Subsequently, meticulous data cleaning and organization procedures were implemented to refine the dataset. The primary data, in its raw form before annotation into a question - and - answer format, was predominantly in the Indonesian language.
Following this, a comprehensive annotation process was conducted to enrich the dataset with specific admission - related information, transforming it into secondary data. Both primary and secondary data predominantly remained in the Indonesian language.