地球资源数据云——数据资源详情
药品消费分类
该数据集《 Drug Consumption Classification》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Database contains records for 1885 respondents with detailed meta information 任务类型：文本多分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 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：drug_consumption.csv。 Read Attribute Information to understand the column values Also check the starter notebook where I converted the column values into more meaningful values Context Database contains records for 1885 respondents. For each respondent 12 attributes are known: Personality measurements which include NEO - FFI - R (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness), BIS - 11 (impulsivity), and ImpSS (sensation seeking), level of education, age, gender, country of residence and ethnicity. All input attributes are originally categorical and are quantified. After quantification values of all input features can be considered as real - valued.
摘要概览
该数据集《 Drug Consumption Classification》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Database contains records for 1885 respondents with detailed meta information
任务类型：文本多分类。
建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。
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：drug_consumption.csv。
Read Attribute Information to understand the column values
Also check the starter notebook where I converted the column values into more meaningful values
Context
Database contains records for 1885 respondents. For each respondent 12 attributes are known: Personality measurements which include NEO - FFI - R (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness), BIS - 11 (impulsivity), and ImpSS (sensation seeking), level of education, age, gender, country of residence and ethnicity.
All input attributes are originally categorical and are quantified. After quantification values of all input features can be considered as real - valued.