Adult income dataset

An individual’s annual income results from various factors. Intuitively, it is influenced by the individual’s education level, age, gender, occupation, and etc.

This is a widely cited KNN dataset. I encountered it during my course, and I wish to share it here because it is a good starter example for data pre-processing and machine learning practices.

**Fields**
The dataset contains 16 columns
Target filed: Income
-- The income is divide into two classes: <=50K and >50K
Number of attributes: 14
-- These are the demographics and other features to describe a person

We can explore the possibility in predicting income level based on the individual’s personal information.

**Acknowledgements**
This dataset named “adult” is found in the UCI machine learning repository
[http://www.cs.toronto.edu/~delve/data/adult/desc.html][1]

The detailed description on the dataset can be found in the original UCI documentation
[http://www.cs.toronto.edu/~delve/data/adult/adultDetail.html][2]

[1]: http://www.cs.toronto.edu/~delve/data/adult/desc.html
[2]: http://www.cs.toronto.edu/~delve/data/adult/adultDetail.html

个体年度收入受多种因素影响。直观而言，其受个人教育水平、年龄、性别、职业等因素之影响。该数据集系KNN类型数据集之典范，广受学界引用。本人于课程学习中邂逅此数据集，愿在此与大家分享，因其堪称数据预处理与机器学习实践之优良入门实例。

**字段说明**
本数据集包含16列数据。
目标字段：收入
-- 收入被划分为两个类别：<=50K与>50K
属性数量：14
-- 这些属性包括人口统计学特征及其他描述个人之特征。

我们可以探讨基于个人信息的预测收入水平的可能性。

**致谢**
本数据集命名为“adult”，收录于UCI机器学习数据库[1]。详细描述可参考原始UCI文档[2]。

[1]: http://www.cs.toronto.edu/~delve/data/adult/desc.html
[2]: http://www.cs.toronto.edu/~delve/data/adult/adultDetail.html