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Adapted from

1. Title: Mushroom Database

2. Sources: 
    (a) Mushroom records drawn from The Audubon Society Field Guide to North
        American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred
        A. Knopf
    (b) Donor: Jeff Schlimmer (
    (c) Date: 27 April 1987

3. Past Usage:
    1. Schlimmer,J.S. (1987). Concept Acquisition Through Representational
       Adjustment (Technical Report 87-19).  Doctoral disseration, Department
       of Information and Computer Science, University of California, Irvine.
       --- STAGGER: asymptoted to 95% classification accuracy after reviewing
           1000 instances.
    2. Iba,W., Wogulis,J., & Langley,P. (1988).  Trading off Simplicity
       and Coverage in Incremental Concept Learning. In Proceedings of 
       the 5th International Conference on Machine Learning, 73-79.
       Ann Arbor, Michigan: Morgan Kaufmann.  
       -- approximately the same results with their HILLARY algorithm    
    3. In the following references a set of rules (given below) were
	learned for this data set which may serve as a point of
	comparison for other researchers.

	Duch W, Adamczak R, Grabczewski K (1996) Extraction of logical rules
	from training data using backpropagation networks, in: Proc. of the
	The 1st Online Workshop on Soft Computing, 19-30.Aug.1996, pp. 25-30,
	available on-line at:

	Duch W, Adamczak R, Grabczewski K, Ishikawa M, Ueda H, Extraction of
	crisp logical rules using constrained backpropagation networks -
	comparison of two new approaches, in: Proc. of the European Symposium
	on Artificial Neural Networks (ESANN'97), Bruge, Belgium 16-18.4.1997,
	pp. xx-xx

	Wlodzislaw Duch, Department of Computer Methods, Nicholas Copernicus
	University, 87-100 Torun, Grudziadzka 5, Poland
	Date: Mon, 17 Feb 1997 13:47:40 +0100
	From: Wlodzislaw Duch <>
	Organization: Dept. of Computer Methods, UMK

	I have attached a file containing logical rules for mushrooms.
	It should be helpful for other people since only in the last year I
	have seen about 10 papers analyzing this dataset and obtaining quite
	complex rules. We will try to contribute other results later.

	With best regards, Wlodek Duch

	Logical rules for the mushroom data sets.

	Logical rules given below seem to be the simplest possible for the
	mushroom dataset and therefore should be treated as benchmark results.

	Disjunctive rules for poisonous mushrooms, from most general
	to most specific:

	P_1) odor=NOT(almond.OR.anise.OR.none)
	     120 poisonous cases missed, 98.52% accuracy

	P_2) spore-print-color=green
	     48 cases missed, 99.41% accuracy
	P_3) odor=none.AND.stalk-surface-below-ring=scaly.AND.
	     8 cases missed, 99.90% accuracy
	P_4) habitat=leaves.AND.cap-color=white
	         100% accuracy     

	Rule P_4) may also be

	P_4') population=clustered.AND.cap_color=white

	These rule involve 6 attributes (out of 22). Rules for edible
	mushrooms are obtained as negation of the rules given above, for
	example the rule:


	gives 48 errors, or 99.41% accuracy on the whole dataset.

	Several slightly more complex variations on these rules exist,
	involving other attributes, such as gill_size, gill_spacing,
	stalk_surface_above_ring, but the rules given above are the simplest
	we have found.

4. Relevant Information:
    This data set includes descriptions of hypothetical samples
    corresponding to 23 species of gilled mushrooms in the Agaricus and
    Lepiota Family (pp. 500-525).  Each species is identified as
    definitely edible, definitely poisonous, or of unknown edibility and
    not recommended.  This latter class was combined with the poisonous
    one.  The Guide clearly states that there is no simple rule for
    determining the edibility of a mushroom; no rule like ``leaflets
    three, let it be'' for Poisonous Oak and Ivy.

5. Number of Instances: 8124

6. Number of Attributes: 22 (all nominally valued)

7. Attribute Information: (classes: edible=e, poisonous=p)
     1. cap-shape:                bell=b,conical=c,convex=x,flat=f,
     2. cap-surface:              fibrous=f,grooves=g,scaly=y,smooth=s
     3. cap-color:                brown=n,buff=b,cinnamon=c,gray=g,green=r,
     4. bruises?:                 bruises=t,no=f
     5. odor:                     almond=a,anise=l,creosote=c,fishy=y,foul=f,
     6. gill-attachment:          attached=a,descending=d,free=f,notched=n
     7. gill-spacing:             close=c,crowded=w,distant=d
     8. gill-size:                broad=b,narrow=n
     9. gill-color:               black=k,brown=n,buff=b,chocolate=h,gray=g,
    10. stalk-shape:              enlarging=e,tapering=t
    11. stalk-root:               bulbous=b,club=c,cup=u,equal=e,
    12. stalk-surface-above-ring: fibrous=f,scaly=y,silky=k,smooth=s
    13. stalk-surface-below-ring: fibrous=f,scaly=y,silky=k,smooth=s
    14. stalk-color-above-ring:   brown=n,buff=b,cinnamon=c,gray=g,orange=o,
    15. stalk-color-below-ring:   brown=n,buff=b,cinnamon=c,gray=g,orange=o,
    16. veil-type:                partial=p,universal=u
    17. veil-color:               brown=n,orange=o,white=w,yellow=y
    18. ring-number:              none=n,one=o,two=t
    19. ring-type:                cobwebby=c,evanescent=e,flaring=f,large=l,
    20. spore-print-color:        black=k,brown=n,buff=b,chocolate=h,green=r,
    21. population:               abundant=a,clustered=c,numerous=n,
    22. habitat:                  grasses=g,leaves=l,meadows=m,paths=p,

8. Missing Attribute Values: 2480 of them (denoted by "?"), all for
   attribute #11.

9. Class Distribution: 
    --    edible: 4208 (51.8%)
    -- poisonous: 3916 (48.2%)
    --     total: 8124 instances