australian: Australian Credit Approval

In fmf: Fast Class Noise Detector with Multi-Factor-Based Learning

Description

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.

Usage

data(australian)

Format

A data frame with 690 Instances and 15 attributes (including the class attribute, "Class")

Details

There are 6 numerical and 8 categorical attributes, all normalized to [-1,1]. The original formatting was as follows: A1: A,B class attribute (formerly: +,-) A2: 0,1 CATEGORICAL (formerly: a,b) A3: continuous. A4: continuous. A5: 1,2,3 CATEGORICAL (formerly: p,g,gg) A6: 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) A7: 1, 2,3, 4,5,6,7,8,9 CATEGORICAL (formerly: ff,dd,j,bb,v,n,o,h,z) A8: continuous. A9: 1, 0 CATEGORICAL (formerly: t, f) A10: 1, 0 CATEGORICAL (formerly: t, f) A11: continuous. A12: 1, 0 CATEGORICAL (formerly t, f) A13: 1, 2, 3 CATEGORICAL (formerly: s, g, p) A14: continuous. A15: continuous.

Source

Confidential. Donated by Ross Quinlan

References

[LibSVM] (https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html), UCI - 1987

Examples

data(australian)

X = australian[, -1]

y = australian[, 1]

fmf documentation built on Sept. 3, 2020, 9:07 a.m.