Australian
OpenML dataset with id 40981
No author found.
Full work available at URL: https://api.openml.org/data/v1/download/18151910/Australian.arff
Upload date: 4 December 2017
Dataset Characteristics
Number of classes: 2
Number of features: 15 (numeric: 6, symbolic: 9 and in total binary: 5 )
Number of instances: 690
Number of instances with missing values: 0
Number of missing values: 0
Author: Confidential. Donated by Ross Quinlan Source: LibSVM, UCI) - 1987 Please cite: UCI
Important note: This dataset is derived from credit-approval, even though both datasets exist individually on UCI. In this version, missing values were filled in (not clear how) and a duplicate feature was removed.
Australian Credit Approval. This is the famous Australian Credit Approval dataset, originating from the StatLog project. It concerns credit card applications. All attribute names and values have been changed to meaningless symbols to protect the confidentiality of the data.
This dataset was retrieved 2014-11-14 from the UCI site and converted to the ARFF format.
__Major changes w.r.t. version 3: dataset from UCI that matches description and data types__
Feature information
There are 6 numerical and 8 categorical attributes, all normalized to [-1,1]. The original formatting was as follows:
A1: 0,1 CATEGORICAL (formerly: a,b) A2: continuous. A3: continuous. A4: 1,2,3 CATEGORICAL (formerly: p,g,gg) A5: 1, 2,3,4,5, 6,7,8,9,10,11,12,13,14 CATEGORICAL (formerly: ff,d,i,k,j,aa,m,c,w, e, q, r,cc, x) A6: 1, 2,3, 4,5,6,7,8,9 CATEGORICAL (formerly: ff,dd,j,bb,v,n,o,h,z) A7: continuous. A8: 1, 0 CATEGORICAL (formerly: t, f) A9: 1, 0 CATEGORICAL (formerly: t, f) A10: continuous. A11: 1, 0 CATEGORICAL (formerly t, f) A12: 1, 2, 3 CATEGORICAL (formerly: s, g, p) A13: continuous. A14: continuous. A15: 1,2 class attribute (formerly: +,-)
Relevant Papers
Ross Quinlan. "Simplifying decision trees", Int J Man-Machine Studies 27, Dec 1987, pp. 221-234.
Ross Quinlan. "C4.5: Programs for Machine Learning", Morgan Kaufmann, Oct 1992
This page was built for dataset: Australian
