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Credit Approval Data Set
Download: Data Folder, Data Set Description

Abstract: This data concerns credit card applications; good mix of attributes

Data Set Characteristics:  

Multivariate

Number of Instances:

690

Area:

Financial

Attribute Characteristics:

Categorical, Integer, Real

Number of Attributes:

15

Date Donated

N/A

Associated Tasks:

Classification

Missing Values?

Yes

Number of Web Hits:

675689


Source:

(confidential source)

Submitted by quinlan '@' cs.su.oz.au


Data Set 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.


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)


Relevant Papers:

Quinlan. "Simplifying decision trees", Int J Man-Machine Studies 27, Dec 1987, pp. 221-234.
[Web Link]

Quinlan. "C4.5: Programs for Machine Learning", Morgan Kaufmann, Oct 1992
[Web Link]


Papers That Cite This Data Set1:

Xiaoming Huo. FBP: A Frontier-Based Tree-Pruning Algorithm. Seoung Bum Kim. 2002. [View Context].

Lorne Mason and Peter L. Bartlett and Jonathan Baxter. Improved Generalization Through Explicit Optimization of Margins. Machine Learning, 38. 2000. [View Context].

Kagan Tumer and Joydeep Ghosh. Robust Combining of Disparate Classifiers through Order Statistics. CoRR, csLG/9905013. 1999. [View Context].

Lorne Mason and Peter L. Bartlett and Jonathan Baxter. Direct Optimization of Margins Improves Generalization in Combined Classifiers. NIPS. 1998. [View Context].


Citation Request:

Please refer to the Machine Learning Repository's citation policy


[1] Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info

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