Summary

UCI boston housing data

License

unknown (from Weka repository)

Dependencies

Tags

arff slurped Weka

Attribute Types

Integer,Floating Point

Download

# Instances: 506 / # Attributes: 14
HDF5 (59.7 KB) XML CSV ARFF LibSVM Matlab Octave

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Original Data Format

arff

Name

'housing'

Version mldata

0

Comment

1. Title: Boston Housing Data

2. Sources: (a) Origin: This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. (b) Creator: Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978. (c) Date: July 7, 1993

3. Past Usage:

4. Used in Belsley, Kuh & Welsch, 'Regression diagnostics ...', Wiley,

   1. N.B. Various transformations are used in the table on pages 244-261.
   2. 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.

5. Relevant Information:

Concerns housing values in suburbs of Boston.

1. Number of Instances: 506

2. Number of Attributes: 13 continuous attributes (including "class" attribute "MEDV"), 1 binary-valued attribute.

3. Attribute Information:

   1. CRIM per capita crime rate by town
   2. ZN proportion of residential land zoned for lots over 25,000 sq.ft.
   3. INDUS proportion of non-retail business acres per town
   4. CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)
   5. NOX nitric oxides concentration (parts per 10 million)
   6. RM average number of rooms per dwelling
   7. AGE proportion of owner-occupied units built prior to 1940
   8. DIS weighted distances to five Boston employment centres
   9. RAD index of accessibility to radial highways
   10. TAX full-value property-tax rate per $10,000
   11. PTRATIO pupil-teacher ratio by town
   12. B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
   13. LSTAT % lower status of the population
   14. MEDV Median value of owner-occupied homes in $1000's

4. Missing Attribute Values: None.

Names

CRIM,ZN,INDUS,CHAS,NOX,RM,AGE,DIS,RAD,TAX,

Types

1. numeric
2. numeric
3. numeric
4. nominal:0,1
5. numeric
6. numeric
7. numeric
8. numeric
9. numeric
10. numeric

Data (first 10 data points)

CRIM	ZN	INDUS	CHAS	NOX	RM	AGE	DIS	RAD	TAX	...
0.00...	18	2.31	0	0.538	6.575	65.2	4.09	1	296	...
0.02...	0	7.07	0	0.469	6.421	78.9	4.9671	2	242	...
0.02...	0	7.07	0	0.469	7.185	61.1	4.9671	2	242	...
0.03...	0	2.18	0	0.458	6.998	45.8	6.0622	3	222	...
0.06...	0	2.18	0	0.458	7.147	54.2	6.0622	3	222	...
0.02...	0	2.18	0	0.458	6.43	58.7	6.0622	3	222	...
0.08...	12	7.87	0	0.524	6.012	66.6	5.5605	5	311	...
0.14...	12	7.87	0	0.524	6.172	96.1	5.9505	5	311	...
0.21...	12	7.87	0	0.524	5.631	100.0	6.0821	5	311	...
0.17...	12	7.87	0	0.524	6.004	85.9	6.5921	5	311	...
...	...	...	...	...	...	...	...	...	...	...

Description

A jarfile containing 30 regression datasets collected by Luis Torgo (regression-datasets.jar, 10,090,266 Bytes).

URLs

http://archive.ics.uci.edu/ml/datasets/Housing

Publications

Data Source

Originally from the UCI machine learning repository.

Measurement Details

From the UCI repository:

1. Title: Boston Housing Data

2. Sources: (a) Origin: This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. (b) Creator: Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978. (c) Date: July 7, 1993

3. Past Usage:

4. Used in Belsley, Kuh & Welsch, 'Regression diagnostics ...', Wiley,

   1. N.B. Various transformations are used in the table on pages 244-261.
   2. 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.

5. Relevant Information:

Concerns housing values in suburbs of Boston.

1. Number of Instances: 506

2. Number of Attributes: 13 continuous attributes (including "class" attribute "MEDV"), 1 binary-valued attribute.

3. Attribute Information:

   1. CRIM per capita crime rate by town
   2. ZN proportion of residential land zoned for lots over 25,000 sq.ft.
   3. INDUS proportion of non-retail business acres per town
   4. CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)
   5. NOX nitric oxides concentration (parts per 10 million)
   6. RM average number of rooms per dwelling
   7. AGE proportion of owner-occupied units built prior to 1940
   8. DIS weighted distances to five Boston employment centres
   9. RAD index of accessibility to radial highways
   10. TAX full-value property-tax rate per $10,000
   11. PTRATIO pupil-teacher ratio by town
   12. B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks by town
   13. LSTAT % lower status of the population
   14. MEDV Median value of owner-occupied homes in $1000's

4. Missing Attribute Values: None.

Usage Scenario

Predict the median value of home from all other variables.

revision 1

by mldata on 2010-11-06 09:58

revision 2

by cong on 2011-09-14 15:17

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Tasks defined on dataset regression-datasets housing

• boston housing regression 2010-11-28 16:04