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analcatdata_impeach

analcatdata_impeach

active ARFF Publicly available Visibility: public Uploaded 29-09-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two versions of each of 84 data sets, plus this README file. Each data set is given in comma-delimited ASCII (.csv) form, and Microsoft Excel (.xls) form. NOTICE: These data sets may be used freely for scientific, educational and/or noncommercial purposes, provided suitable acknowledgment is given (by citing the above-named reference). Further details concerning the book, including information on statistical software (including sample S-PLUS/R and SAS code), are available at the web site http://www.stern.nyu.edu/~jsimonof/AnalCatData Information about the dataset CLASSTYPE: numeric CLASSINDEX: none specific Note: Quotes, Single-Quotes and Backslashes were removed, Blanks replaced with Underscores

10 features

Name (ignore)nominal100 unique values
0 missing
Statenominal50 unique values
0 missing
Perjury.guiltynominal2 unique values
0 missing
Obstruction.guiltynominal2 unique values
0 missing
Total.guiltynominal3 unique values
0 missing
Partynominal2 unique values
0 missing
Conservatismnumeric28 unique values
0 missing
Clinton.vote.1996numeric24 unique values
0 missing
Reelection.yearnominal3 unique values
0 missing
First.termnominal2 unique values
0 missing
Won.state.1996nominal2 unique values
0 missing

19 properties

100
Number of instances (rows) of the dataset.
10
Number of attributes (columns) of the dataset.
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.
2
Number of numeric attributes.
8
Number of nominal attributes.
50
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.
0.1
Number of attributes divided by the number of instances.
20
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
80
Percentage of nominal attributes.
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.
5
Number of binary attributes.

11 tasks

0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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