Boston波士顿房价数据集的简介
该数据集包含美国人口普查局收集的美国马萨诸塞州波士顿住房价格的有关信息, 数据集很小，只有506个案例。
数据集都有以下14个属性:
CRIM--城镇人均犯罪率 ------【城镇人均犯罪率】
ZN - 占地面积超过25,000平方英尺的住宅用地比例。 ------【住宅用地所占比例】
INDUS - 每个城镇非零售业务的比例。 ------【城镇中非商业用地占比例】
CHAS - Charles River虚拟变量（如果是河道，则为1;否则为0 ------【查尔斯河虚拟变量，用于回归分析】
NOX - 一氧化氮浓度（每千万份） ------【环保指标】
RM - 每间住宅的平均房间数 ------【每栋住宅房间数】
AGE - 1940年以前建造的自住单位比例 ------【1940年以前建造的自住单位比例 】
DIS -波士顿的五个就业中心加权距离 ------【与波士顿的五个就业中心加权距离】
RAD - 径向高速公路的可达性指数 ------【距离高速公路的便利指数】
TAX - 每10,000美元的全额物业税率 ------【每一万美元的不动产税率】
PTRATIO - 城镇的学生与教师比例 ------【城镇中教师学生比例】
B - 1000（Bk - 0.63）^ 2其中Bk是城镇黑人的比例 ------【城镇中黑人比例】
LSTAT - 人口状况下降％ ------【房东属于低等收入阶层比例】
MEDV - 自有住房的中位数报价, 单位1000美元 ------【自住房屋房价中位数】
Boston波士顿房价数据集的下载
下载地址：https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data
from sklearn.datasets import load_boston
boston = load_boston()
print(boston.DESCR)
Boston House Prices dataset
===========================
Notes
------
Data Set Characteristics:
:Number of Instances: 506
:Number of Attributes: 13 numeric/categorical predictive
:Median Value (attribute 14) is usually the target
:Attribute Information (in order):
- CRIM per capita crime rate by town
- ZN proportion of residential land zoned for lots over 25,000 sq.ft.
- INDUS proportion of non-retail business acres per town
- CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)
- NOX nitric oxides concentration (parts per 10 million)
- RM average number of rooms per dwelling
- AGE proportion of owner-occupied units built prior to 1940
- DIS weighted distances to five Boston employment centres
- RAD index of accessibility to radial highways
- TAX full-value property-tax rate per $10,000
- PTRATIO pupil-teacher ratio by town
- B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
- LSTAT % lower status of the population
- MEDV Median value of owner-occupied homes in $1000's
:Missing Attribute Values: None
:Creator: Harrison, D. and Rubinfeld, D.L.
This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.
The Boston house-price data of Harrison, D. and Rubinfeld, D.L. 'Hedonic
prices and the demand for clean air', J. Environ. Economics & Management,
vol.5, 81-102, 1978. Used in Belsley, Kuh & Welsch, 'Regression diagnostics
...', Wiley, 1980. N.B. Various transformations are used in the table on
pages 244-261 of the latter.
The Boston house-price data has been used in many machine learning papers that address regression
problems.
**References**
- Belsley, Kuh & Welsch, 'Regression diagnostics: Identifying Influential Data and Sources of Collinearity', Wiley, 1980. 244-261.
- Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning. In Proceedings on the Tenth International Conference of Machine Learning, 236-243, University of Massachusetts, Amherst. Morgan Kaufmann.
- many more! (see http://archive.ics.uci.edu/ml/datasets/Housing)
