地球资源数据云——数据资源详情
天气类型分类
该数据集《Weather Type Classification》主要用于多分类任务，数据形态以表格为主。 题目说明：Forecast with Precision: Simulated Data for Predicting Weather Types 任务类型：表格多分类。 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：weather_classification_data.csv。 Description This dataset is synthetically generated to mimic weather data for classification tasks. It includes various weather - related features and categorizes the weather into four types: Rainy, Sunny, Cloudy, and Snowy. This dataset is designed for practicing classification algorithms, data preprocessing, and outlier detection methods. Variables Temperature (numeric): The temperature in degrees Celsius, ranging from extreme cold to extreme heat. Humidity (numeric): The humidity percentage, including values above 100% to introduce outliers. Wind Speed (numeric): The wind speed in kilometers per hour, with a range including unrealistically high values.
摘要概览
该数据集《Weather Type Classification》主要用于多分类任务，数据形态以表格为主。 题目说明：Forecast with Precision: Simulated Data for Predicting Weather Types
任务类型：表格多分类。
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：weather_classification_data.csv。
Description This dataset is synthetically generated to mimic weather data for classification tasks. It includes various weather - related features and categorizes the weather into four types: Rainy, Sunny, Cloudy, and Snowy. This dataset is designed for practicing classification algorithms, data preprocessing, and outlier detection methods.
Variables
Temperature (numeric): The temperature in degrees Celsius, ranging from extreme cold to extreme heat.
Humidity (numeric): The humidity percentage, including values above 100% to introduce outliers.
Wind Speed (numeric): The wind speed in kilometers per hour, with a range including unrealistically high values.