机器学习_MushroomDataSet（蘑菇数据集）
Mushroom Data Set(蘑菇数据集)
数据摘要：
From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible 中⽂关键词：
机器学习，蘑菇，分类，多变量,UCI,
英⽂关键词：
Machine Learning,Mushroom,Classification,MultiVarite,UCI,
数据格式：
TEXT
唯美图片壁纸>淫羊藿功能数据⽤途：
This data is ud for classification.
数据详细介绍：
Mushroom Data Set
Abstract:
From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible
Source:
Origin:
Mushroom records drawn from The Audubon Society Field Guide to North American Mushrooms (1981). G. H. Lincoff (Pres.), New York: Alfred A. Knopf
Donor:
Jeff Schlimmer (Jeffrey.Schlimmer '@' /doc/c4ca1c21aaea998fcc220e1c.html )
儿童心理学书籍
Data Set Information:
This data t 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.
Attribute Information:
1. cap-shape: bell=b,conical=c,convex=x,flat=f, knobbed=k,sunken=s
2. cap-surface: fibrous=f,grooves=g,scaly=y,smooth=s
3. cap-color: brown=n,buff=b,cinnamon=c,gray=g,green=r,
pink=p,purple=u,red=e,white=w,yellow=y
4. bruis?: bruis=t,no=f
5. odor: almond=a,ani=l,creosote=c,fishy=y,foul=f, musty=m,none=n,pungent=p,spicy=s
6. gill-attachment: attached=a,descending=d,free=f,notched=n
7. gill-spacing: clo=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,
green=r,orange=o,pink=p,purple=u,red=e, white=w,yellow=y
10. stalk-shape: enlarging=e,tapering=t
11. stalk-root: bulbous=b,club=c,cup=u,equal=e, rhizomorphs=z,rooted=r,missing=?
12. stalk-surface-above-ring: fibrous=f,scaly=y,silky=k,smooth=s
深圳职业技术学院分数线
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,
pink=p,red=e,white=w,yellow=y
15. stalk-color-below-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o,向左转
pink=p,red=e,white=w,yellow=y
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,
none=n,pendant=p,sheathing=s,zone=z
20. spore-print-color: black=k,brown=n,buff=b,chocolate=h,green=r,
有理不在声高
orange=o,purple=u,white=w,yellow=y
21. population: abundant=a,clustered=c,numerous=n, scattered=s,veral=v,solitary=y
22. habitat: grass=g,leaves=l,meadows=m,paths=p, urban=u,waste=w,woods=d Relevant Papers:
Schlimmer,J.S. (1987). Concept Acquisition Through Reprentational Adjustment (Technical Report 87-19). Doctoral disration, Department of Information and Computer Science, University of California, Irvine.
[Web Link]
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.
[Web Link]
如何辨别天珠
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, [Web Link]
[Web Link]
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.
[Web Link]
数据预览：
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