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Summary

UCI boston housing data (scaled to [-1,1])

License
unknown (from LibSVMTools repository)
Dependencies
Tags
libsvm LibSVMTools slurped
Attribute Types
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# Instances: 506 / # Attributes: 14
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Original Data Format
libsvm
Name
housing_scale
Version mldata
0
Comment

LibSVM

Names
Data (first 10 data points)
    24 -1.0 -0.64 -0.86... -1.0 -0.37... 0.15... 0.28... -0.46... -1.0 ...
    21 -0.99... -1.0 -0.51... -1.0 -0.65... 0.09... 0.56... -0.30... -0.91... ...
    34 -0.99... -1.0 -0.51... -1.0 -0.65... 0.38... 0.19... -0.30... -0.91... ...
    33 -0.99... -1.0 -0.87... -1.0 -0.69... 0.31... -0.11... -0.10... -0.82... ...
    36 -0.99... -1.0 -0.87... -1.0 -0.69... 0.37... 0.05... -0.10... -0.82... ...
    28 -0.99... -1.0 -0.87... -1.0 -0.69... 0.09... 0.14... -0.10... -0.82... ...
    22 -0.99... -0.75 -0.45... -1.0 -0.42... -0.06... 0.31... -0.19... -0.65... ...
    27 -0.99... -0.75 -0.45... -1.0 -0.42... 0.00... 0.91... -0.12... -0.65... ...
    16 -0.99... -0.75 -0.45... -1.0 -0.42... -0.20... 1.0 -0.09... -0.65... ...
    18 -0.99... -0.75 -0.45... -1.0 -0.42... -0.06... 0.70... -0.00... -0.65... ...
    ... ... ... ... ... ... ... ... ... ... ...
Description

This is a normalized (scaled to [-1,1]) version of the boston housing regression dataset.

See also: http://mldata.org/repository/data/viewslug/regression-datasets-housing/

URLs
http://archive.ics.uci.edu/ml/datasets/Housing
Publications
    Data Source
    http://www.ics.uci.edu/~mlearn/MLRepository.html UCI / Housing (Boston)
    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 2010-11-01 11:49
    revision 2
    by cong on 2011-09-14 16:22

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