adding more description to the nursery notebook

Author: mahaalbashir

data/nursery.arff

@@ -1,32 +1,32 @@
 % 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 
-% 
+%    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
@@ -38,10 +38,10 @@
 %    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
@@ -55,30 +55,30 @@
 %    . 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 
+%    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
@@ -87,11 +87,11 @@
 %    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 %)
@@ -13078,4 +13078,3 @@ great_pret,very_crit,foster,more,critical,inconv,slightly_prob,not_recom,not_rec
 great_pret,very_crit,foster,more,critical,inconv,problematic,recommended,spec_prior
 great_pret,very_crit,foster,more,critical,inconv,problematic,priority,spec_prior
 great_pret,very_crit,foster,more,critical,inconv,problematic,not_recom,not_recom
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