Data
abalone

abalone

active ARFF Publicly available Visibility: public Uploaded 01-06-2015 by Rafael G. Mantovani
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Author: Source: [original](http://www.openml.org/d/183) - UCI Please cite: * Abstract: A 3-class version of abalone dataset. * Sources: (a) Original owners of database: Marine Resources Division Marine Research Laboratories - Taroona Department of Primary Industry and Fisheries, Tasmania GPO Box 619F, Hobart, Tasmania 7001, Australia (contact: Warwick Nash +61 02 277277, wnash@dpi.tas.gov.au) (b) Donor of database: Sam Waugh (Sam.Waugh@cs.utas.edu.au) Department of Computer Science, University of Tasmania GPO Box 252C, Hobart, Tasmania 7001, Australia

9 features

Class (target)nominal3 unique values
0 missing
V1nominal3 unique values
0 missing
V2numeric134 unique values
0 missing
V3numeric111 unique values
0 missing
V4numeric51 unique values
0 missing
V5numeric2429 unique values
0 missing
V6numeric1515 unique values
0 missing
V7numeric880 unique values
0 missing
V8numeric926 unique values
0 missing

19 properties

4177
Number of instances (rows) of the dataset.
9
Number of attributes (columns) of the dataset.
3
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.
7
Number of numeric attributes.
2
Number of nominal attributes.
31.67
Percentage of instances belonging to the least frequent class.
1323
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.58
Average class difference between consecutive instances.
0
Percentage of missing values.
0
Number of attributes divided by the number of instances.
77.78
Percentage of numeric attributes.
34.64
Percentage of instances belonging to the most frequent class.
22.22
Percentage of nominal attributes.
1447
Number of instances belonging to the most frequent class.

5 tasks

90 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
49 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
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