Data
CPS1988

CPS1988

active ARFF Publicly available Visibility: public Uploaded 16-06-2022 by Sebastian Fischer
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Source This dataset was obtained from the AER R package (see citation request below). Data description Cross-section data originating from the March 1988 Current Population Survey by the US Census Bureau. The data is a sample of men aged 18 to 70 with positive annual income greater than USD 50 in 1992, who are not self-employed nor working without pay. Wages are deflated by the deflator of Personal Consumption Expenditure for 1992. A problem with CPS data is that it does not provide actual work experience. It is therefore customary to compute experience as age - education - 6 (as was done by Bierens and Ginther, 2001), this may be considered potential experience. As a result, some respondents have negative experience Attribute Information * wage Wage (in dollars per week). * education Number of years of education. * experience Number of years of potential work experience. * ethnicity Factor with levels "cauc" and "afam" (African-American). * smsa Factor. Does the individual reside in a Standard Metropolitan Statistical Area (SMSA)? * region Factor with levels "northeast", "midwest", "south", "west". * parttime Factor. Does the individual work part-time? Citation Request Christian Kleiber and Achim Zeileis (2008). Applied Econometrics with R. New York: Springer-Verlag. ISBN 978-0-387-77316-2. URL https://CRAN.R-project.org/package=AER *Bibtex* @book{kleiber2008applied, title={Applied econometrics with R}, author={Kleiber, Christian and Zeileis, Achim}, year={2008}, publisher={Springer Science \& Business Media} }

7 features

wage (target)numeric5970 unique values
0 missing
educationnumeric19 unique values
0 missing
experiencenumeric67 unique values
0 missing
ethnicitynominal2 unique values
0 missing
smsanominal2 unique values
0 missing
regionnominal4 unique values
0 missing
parttimenominal2 unique values
0 missing

19 properties

28155
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
3
Number of numeric attributes.
4
Number of nominal attributes.
42.86
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
-389.44
Average class difference between consecutive instances.
42.86
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
57.14
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
3
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 5 times 2-fold Crossvalidation - target_feature: wage
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