地球资源数据云——数据资源详情
超市销售数据集
该数据集《Superstore Sales Dataset》主要用于回归/预测任务，数据形态以文本为主。 题目说明：Predict Sales using Time Series 任务类型：文本回归/预测。 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：train.csv。 Context Retail dataset of a global superstore for 4 years. Perform EDA and Predict the sales of the next 7 days from the last date of the Training dataset! Content Time series analysis deals with time series based data to extract patterns for predictions and other characteristics of the data. It uses a model for forecasting future values in a small time frame based on previous observations. It is widely used for non - stationary data, such as economic data, weather data, stock prices, and retail sales forecasting. Dataset The dataset is easy to understand and is self - explanatory
摘要概览
该数据集《Superstore Sales Dataset》主要用于回归/预测任务，数据形态以文本为主。 题目说明：Predict Sales using Time Series
任务类型：文本回归/预测。
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：train.csv。
Context
Retail dataset of a global superstore for 4 years. Perform EDA and Predict the sales of the next 7 days from the last date of the Training dataset!
Content
Time series analysis deals with time series based data to extract patterns for predictions and other characteristics of the data. It uses a model for forecasting future values in a small time frame based on previous observations. It is widely used for non - stationary data, such as economic data, weather data, stock prices, and retail sales forecasting.
Dataset The dataset is easy to understand and is self - explanatory