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metadata.txt
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metadata.txt
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1. Title: Credit Approval
2. Sources:
(confidential)
Submitted by quinlan@cs.su.oz.au
3. Past Usage:
See Quinlan,
* "Simplifying decision trees", Int J Man-Machine Studies 27,
Dec 1987, pp. 221-234.
* "C4.5: Programs for Machine Learning", Morgan Kaufmann, Oct 1992
4. Relevant Information:
This file concerns credit card applications. All attribute names
and values have been changed to meaningless symbols to protect
confidentiality of the data.
This dataset is interesting because there is a good mix of
attributes -- continuous, nominal with small numbers of
values, and nominal with larger numbers of values. There
are also a few missing values.
5. Number of Instances: 690
6. Number of Attributes: 15 + class attribute
7. Attribute Information:
A1: b, a.
A2: continuous.
A3: continuous.
A4: u, y, l, t.
A5: g, p, gg.
A6: c, d, cc, i, j, k, m, r, q, w, x, e, aa, ff.
A7: v, h, bb, j, n, z, dd, ff, o.
A8: continuous.
A9: t, f.
A10: t, f.
A11: continuous.
A12: t, f.
A13: g, p, s.
A14: continuous.
A15: continuous.
A16: +,- (class attribute)
8. Missing Attribute Values:
37 cases (5%) have one or more missing values. The missing
values from particular attributes are:
A1: 12
A2: 12
A4: 6
A5: 6
A6: 9
A7: 9
A14: 13
9. Class Distribution
+: 307 (44.5%)
-: 383 (55.5%)