地球资源数据云——数据资源详情
葡萄酒品质分级
该数据集《Wine Quality Classification》主要用于多分类任务，数据形态以文本为主。 题目说明：Classify wine samples based on chemical features using ML models. 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：wine_quality_classification.csv。 English: This synthetic dataset is designed for classification tasks involving wine quality. It includes 1,000 samples with key chemical attributes such as acidity, sugar level, alcohol content, and density. Each sample is labeled with a wine quality class: low, medium, or high. Use this dataset to: Train classification models like SVM, XGBoost, and Logistic Regression Explore the impact of chemical features on wine quality
摘要概览
该数据集《Wine Quality Classification》主要用于多分类任务，数据形态以文本为主。 题目说明：Classify wine samples based on chemical features using ML models.
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：wine_quality_classification.csv。
English:
This synthetic dataset is designed for classification tasks involving wine quality. It includes 1,000 samples with key chemical attributes such as acidity, sugar level, alcohol content, and density. Each sample is labeled with a wine quality class: low, medium, or high.
Use this dataset to:
Train classification models like SVM, XGBoost, and Logistic Regression
Explore the impact of chemical features on wine quality