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+Description of the Dataset:
+
+THIS CREDIT DATA ORIGINATES FROM QUINLAN (see below).   
+
+1. Title: Australian 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: 14 + class attribute
+
+7.  Attribute Information:   THERE ARE 6 NUMERICAL AND 8 CATEGORICAL ATTRIBUTES.
+ 
+                             THE LABELS HAVE BEEN CHANGED FOR THE CONVENIENCE
+                             OF THE STATISTICAL ALGORITHMS.   FOR EXAMPLE,
+                             ATTRIBUTE 4 ORIGINALLY HAD 3 LABELS p,g,gg AND
+                             THESE HAVE BEEN CHANGED TO LABELS 1,2,3.
+                             
+
+    A1:	0,1    CATEGORICAL
+        a,b
+    A2:	continuous.
+    A3:	continuous.
+    A4:	1,2,3         CATEGORICAL
+        p,g,gg
+    A5:  1, 2,3,4,5, 6,7,8,9,10,11,12,13,14    CATEGORICAL
+         ff,d,i,k,j,aa,m,c,w, e, q, r,cc, x 
+         
+    A6:	 1, 2,3, 4,5,6,7,8,9    CATEGORICAL
+        ff,dd,j,bb,v,n,o,h,z 
+
+    A7:	continuous.
+    A8:	1, 0       CATEGORICAL
+        t, f.
+    A9: 1, 0	    CATEGORICAL
+        t, f.
+    A10:	continuous.
+    A11:  1, 0	    CATEGORICAL
+          t, f.
+    A12:    1, 2, 3    CATEGORICAL
+            s, g, p 
+    A13:	continuous.
+    A14:	continuous.
+    A15:   1,2
+           +,-         (class attribute)
+
+8.  Missing Attribute Values:
+    37 cases (5%) HAD one or more missing values.  The missing
+    values from particular attributes WERE:
+
+    A1:  12
+    A2:  12
+    A4:   6
+    A5:   6
+    A6:   9
+    A7:   9
+    A14: 13
+    
+    THESE WERE REPLACED BY THE MODE OF THE ATTRIBUTE (CATEGORICAL)
+                               MEAN OF THE ATTRIBUTE (CONTINUOUS)
+                           
+9.  Class Distribution
+  
+    +: 307 (44.5%)    CLASS 2
+    -: 383 (55.5%)    CLASS 1
+
+
+10.  There is no cost matrix.
+