# Info on Credit Approval Data Base

    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%)