MikeGreen2710/standardization_20240822_v2_fixed_1tr1_1tr3

该数据集包含多个特征字段，涵盖了文本、序列、结构化数据等多种数据类型。主要特征包括索引、ID、文本内容、法律信息、引用信息、字符串信息、语言信息、疾病信息、位置信息、战争信息、数字信息、目的信息、食品信息、生活信息、奖励信息、区域信息、车辆信息、前进信息、船舶信息、学生信息、数量信息、年份信息、价格信息、公司信息、无信息、RPI信息、无信息、标题、地址、描述、来源、楼层数、门方向、价格、面积、房屋正面、道路宽度、卧室数量、建造年份、宽度、更新时间、发布日期、行号、标准化后的房屋正面、标准化后的道路宽度、车辆扩展信息、区域扩展信息、标准化后的宽度、标准化后的车辆面积、标准化后的长度、标准化后的区域面积、标准化后的发布日期、标准化后的门方向、标准化后的价格、标准化后的租金价格、标准化后的建造年份、修正后的建造年份、标准化后的建造年份数量、标准化后的楼层信息、最终标准化后的楼层信息、特定类型的标准化信息、土地价格、修正后的土地价格等。数据集包含一个训练集，大小为3290770127字节，包含1323550个样本。

This dataset contains multiple feature fields, covering various data types such as text, sequences, and structured data. The main features include index, ID, text content, legal information (LEG), citation information (CIT), string information (STR), language information (LAN), disease information (DIS), location information (LOC), war information (WAR), numerical information (NUM), purpose information (PUR), food information (FDR), living information (LIV), reward information (RWD), area information (ARA), vehicle information (CAR), forward information (FWD), ship information (SHP), student information (STU), quantity information (NOF), year information (YCT), price information (PRI), company information (COR), no information (NOBA), RPI information (RPI), no information (NOBR), title, address, description, source, number of floors, door direction, price, area, house front, road width, number of bedrooms, built year, width, updated time, post date, row number, standardized house front, standardized road width, vehicle extension information, area extension information, standardized width, standardized vehicle area, standardized length, standardized area area, standardized post date, standardized door direction, standardized price, standardized rental price, standardized built year, fixed built year, standardized number of construction years, standardized floor information, final standardized floor information, specific types of standardized information, land price, fixed land price, etc. The dataset contains a training set with a size of 3290770127 bytes and 1323550 samples.