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