1. Title: Nursery Database

2. Sources:
   (a) Creator: Vladislav Rajkovic et al. (13 experts)
   (b) Donors: Marko Bohanec   (marko.bohanec@ijs.si)
               Blaz Zupan      (blaz.zupan@ijs.si)
   (c) Date: June, 1997

3. Past Usage:

   The hierarchical decision model, from which this dataset is
   derived, was first presented in 

   M. Olave, V. Rajkovic, M. Bohanec: An application for admission in
   public school systems. In (I. Th. M. Snellen and W. B. H. J. van de
   Donk and J.-P. Baquiast, editors) Expert Systems in Public
   Administration, pages 145-160. Elsevier Science Publishers (North
   Holland)}, 1989.

   Within machine-learning, this dataset was used for the evaluation
   of HINT (Hierarchy INduction Tool), which was proved to be able to
   completely reconstruct the original hierarchical model. This,
   together with a comparison with C4.5, is presented in

   B. Zupan, M. Bohanec, I. Bratko, J. Demsar: Machine learning by
   function decomposition. ICML-97, Nashville, TN. 1997 (to appear)

4. Relevant Information Paragraph:

   Nursery Database was derived from a hierarchical decision model
   originally developed to rank applications for nursery schools. It
   was used during several years in 1980's when there was excessive
   enrollment to these schools in Ljubljana, Slovenia, and the
   rejected applications frequently needed an objective
   explanation. The final decision depended on three subproblems:
   occupation of parents and child's nursery, family structure and
   financial standing, and social and health picture of the family.
   The model was developed within expert system shell for decision
   making DEX (M. Bohanec, V. Rajkovic: Expert system for decision
   making. Sistemica 1(1), pp. 145-157, 1990.).

   The hierarchical model ranks nursery-school applications according
   to the following concept structure:

   NURSERY            Evaluation of applications for nursery schools
   . EMPLOY           Employment of parents and child's nursery
   . . parents        Parents' occupation
   . . has_nurs       Child's nursery
   . STRUCT_FINAN     Family structure and financial standings
   . . STRUCTURE      Family structure
   . . . form         Form of the family
   . . . children     Number of children
   . . housing        Housing conditions
   . . finance        Financial standing of the family
   . SOC_HEALTH       Social and health picture of the family
   . . social         Social conditions
   . . health         Health conditions

   Input attributes are printed in lowercase. Besides the target
   concept (NURSERY) the model includes four intermediate concepts:
   EMPLOY, STRUCT_FINAN, STRUCTURE, SOC_HEALTH. Every concept is in
   the original model related to its lower level descendants by a set
   of examples (for these examples sets see 
   http://www-ai.ijs.si/BlazZupan/nursery.html).

   The Nursery Database contains examples with the structural
   information removed, i.e., directly relates NURSERY to the eight input
   attributes: parents, has_nurs, form, children, housing, finance,
   social, health.

   Because of known underlying concept structure, this database may be
   particularly useful for testing constructive induction and
   structure discovery methods.

5. Number of Instances: 12960
   (instances completely cover the attribute space)

6. Number of Attributes: 8

7. Attribute Values:

   parents        usual, pretentious, great_pret
   has_nurs       proper, less_proper, improper, critical, very_crit
   form           complete, completed, incomplete, foster
   children       1, 2, 3, more
   housing        convenient, less_conv, critical
   finance        convenient, inconv
   social         non-prob, slightly_prob, problematic
   health         recommended, priority, not_recom

8. Missing Attribute Values: none

9. Class Distribution (number of instances per class)

   class        N         N[%]
   ------------------------------
   not_recom    4320   (33.333 %)
   recommend       2   ( 0.015 %)
   very_recom    328   ( 2.531 %)
   priority     4266   (32.917 %)
   spec_prior   4044   (31.204 %)