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<title>Balance Scale Weight & Distance Data Base</title>
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<h1>Info on Balance Scale Weight & Distance Data Base</h1>
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1. Title: Balance Scale Weight & Distance Database

2. Source Information: 
    (a) Source: Generated to model psychological experiments reported
		by Siegler, R. S. (1976).  Three Aspects of Cognitive
		Development.  Cognitive Psychology, 8, 481-520.
    (b) Donor: Tim Hume (hume@ics.uci.edu)
    (c) Date: 22 April 1994

3. Past Usage: (possibly different formats of this data)
   - Publications
	1. Klahr, D., & Siegler, R.S. (1978).  The Representation of
	   Children's Knowledge.  In H. W. Reese & L. P. Lipsitt (Eds.),
	   Advances in Child Development and Behavior, pp. 61-116.  New
	   York: Academic Press 
	2. Langley,P. (1987).  A General Theory of Discrimination
	   Learning.  In D. Klahr, P. Langley, & R. Neches (Eds.),
	   Production System Models of Learning and Development, pp.
	   99-161. Cambridge, MA: MIT Press
	3. Newell, A. (1990).  Unified Theories of Cognition.
	   Cambridge, MA: Harvard University Press
	4. McClelland, J.L. (1988).  Parallel Distibuted Processing:
	   Implications for Cognition and Development.  Technical
	   Report AIP-47, Department of Psychology, Carnegie-Mellon
	   University 
	5. Shultz, T., Mareschal, D., & Schmidt, W. (1994).  Modeling
	   Cognitive Development on Balance Scale Phenomena. Machine
	   Learning, Vol. 16, pp. 59-88.

4. Relevant Information: 
	This data set was generated to model psychological
	experimental results.  Each example is classified as having the
	balance scale tip to the right, tip to the left, or be
	balanced.  The attributes are the left weight, the left
	distance, the right weight, and the right distance.  The
	correct way to find the class is the greater of 
	(left-distance * left-weight) and (right-distance *
	right-weight).  If they are equal, it is balanced.

5. Number of Instances: 625 (49 balanced, 288 left, 288 right)

6. Number of Attributes: 4 (numeric) + class name = 5

7. Attribute Information:
	1. Class Name: 3 (L, B, R)
	2. Left-Weight: 5 (1, 2, 3, 4, 5)
	3. Left-Distance: 5 (1, 2, 3, 4, 5)
	4. Right-Weight: 5 (1, 2, 3, 4, 5)
	5. Right-Distance: 5 (1, 2, 3, 4, 5)

8. Missing Attribute Values: 
	none

9. Class Distribution: 
   1. 46.08 percent are L
   2. 07.84 percent are B
   3. 46.08 percent are R
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