地球资源数据云——数据资源详情
葡萄酒类型分类数据集
该数据集《Wine Type Classification Dataset》主要用于二分类任务，数据形态以表格为主。 题目说明：A Combined Dataset of Red and White Wine Characteristics for Type Classification 任务类型：表格二分类。 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：wine_quality_merged.csv。 The Wine Type Classification Dataset contains 6,497 samples of red and white wines, with 13 features describing their chemical properties and quality. The dataset is designed for tasks such as wine type classification (red or white) and quality prediction. Each sample includes the following features: fixed acidity: Fixed acidity level of the wine volatile acidity: Volatile acidity level of the wine citric acid: Citric acid content residual sugar: Amount of residual sugar chlorides: Chloride content free sulfur dioxide: Free sulfur dioxide level total sulfur dioxide: Total sulfur dioxide level density: Density of the wine pH: pH level of the wine sulphates: Sulphate content alcohol: Alcohol percentage quality: Wine quality score (numerical) type: Wine type (Red or White) This dataset is ideal for machine learning tasks such as binary classification (predicting wine type), regression (predicting quality), or exploratory data analysis to uncover relationships between chemical properties and wine characteristics. It combines data from red and white wine datasets, making it a versatile resource for researchers, data scientists, and wine enthusiasts.
摘要概览
该数据集《Wine Type Classification Dataset》主要用于二分类任务，数据形态以表格为主。 题目说明：A Combined Dataset of Red and White Wine Characteristics for Type Classification
任务类型：表格二分类。
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：wine_quality_merged.csv。
The Wine Type Classification Dataset contains 6,497 samples of red and white wines, with 13 features describing their chemical properties and quality. The dataset is designed for tasks such as wine type classification (red or white) and quality prediction. Each sample includes the following features:
fixed acidity: Fixed acidity level of the wine volatile acidity: Volatile acidity level of the wine citric acid: Citric acid content residual sugar: Amount of residual sugar chlorides: Chloride content free sulfur dioxide: Free sulfur dioxide level total sulfur dioxide: Total sulfur dioxide level density: Density of the wine pH: pH level of the wine
sulphates: Sulphate content alcohol: Alcohol percentage quality: Wine quality score (numerical) type: Wine type (Red or White)
This dataset is ideal for machine learning tasks such as binary classification (predicting wine type), regression (predicting quality), or exploratory data analysis to uncover relationships between chemical properties and wine characteristics.
It combines data from red and white wine datasets, making it a versatile resource for researchers, data scientists, and wine enthusiasts.