Credit approval data

Source: R/FFTreesdata_doc.R

This data reports predictors and the result of credit card applications. Its attribute names and values have been changed to symbols to protect confidentiality.

creditapproval

Format

A data frame containing 690 cases (rows) and 15 variables (columns).

c.1

categorical: b, a

c.2

continuous

c.3

continuous

c.4

categorical: u, y, l, t

c.5

categorical: g, p, gg

c.6

categorical: c, d, cc, i, j, k, m, r, q, w, x, e, aa, ff

c.7

categorical: v, h, bb, j, n, z, dd, ff, o

c.8

continuous

c.9

categorical: t, f

c.10

categorical: t, f

c.11

continuous

c.12

categorical: t, f

c.13

categorical: g, p, s

c.14

continuous

c.15

continuous

crit

Criterion: Credit approval.

Values: TRUE (+) vs. FALSE (-) (44.5% vs. 55.5%).

Details

This dataset contains a mix of attributes -- continuous, nominal with small sample sizes, and nominal with larger sample sizes. There are also a few missing values.

We made the following enhancements to the original data for improved usability:

  • Any missing values, denoted as "?" in the dataset, were transformed into NA values.

  • Binary factor variables with exclusive "t" and "f" values were converted to logical vectors (TRUE/FALSE).

Other than that, the data remains consistent with the original dataset.