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Annealing Data Set
Download: Data Folder, Data Set Description

Abstract: Steel annealing data

Data Set Characteristics:  


Number of Instances:




Attribute Characteristics:

Categorical, Integer, Real

Number of Attributes:


Date Donated


Associated Tasks:


Missing Values?


Number of Web Hits:




David Sterling and Wray Buntine

Data Set Information:


Attribute Information:

Attribute Listing:
1. family: --,GB,GK,GS,TN,ZA,ZF,ZH,ZM,ZS
2. product-type: C, H, G
3. steel: -,R,A,U,K,M,S,W,V
4. carbon: continuous
5. hardness: continuous
6. temper_rolling: -,T
7. condition: -,S,A,X
8. formability: -,1,2,3,4,5
9. strength: continuous
10. non-ageing: -,N
11. surface-finish: P,M,-
12. surface-quality: -,D,E,F,G
13. enamelability: -,1,2,3,4,5
14. bc: Y,-
15. bf: Y,-
16. bt: Y,-
17. bw/me: B,M,-
18. bl: Y,-
19. m: Y,-
20. chrom: C,-
21. phos: P,-
22. cbond: Y,-
23. marvi: Y,-
24. exptl: Y,-
25. ferro: Y,-
26. corr: Y,-
27. blue/bright/varn/clean: B,R,V,C,-
28. lustre: Y,-
29. jurofm: Y,-
30. s: Y,-
31. p: Y,-
32. shape: COIL, SHEET
33. thick: continuous
34. width: continuous
35. len: continuous
36. oil: -,Y,N
37. bore: 0000,0500,0600,0760
38. packing: -,1,2,3
classes: 1,2,3,4,5,U

-- The '-' values are actually 'not_applicable' values rather than 'missing_values' (and so can be treated as legal discrete values rather than as showing the absence of a discrete value).

Relevant Papers:


Papers That Cite This Data Set1:

Qingping Tao Ph. D. MAKING EFFICIENT LEARNING ALGORITHMS WITH EXPONENTIALLY MANY FEATURES. Qingping Tao A DISSERTATION Faculty of The Graduate College University of Nebraska In Partial Fulfillment of Requirements. 2004. [View Context].

Yuan Jiang and Zhi-Hua Zhou. Editing Training Data for kNN Classifiers with Neural Network Ensemble. ISNN (1). 2004. [View Context].

Jihoon Yang and Rajesh Parekh and Vasant Honavar. DistAl: An inter-pattern distance-based constructive learning algorithm. Intell. Data Anal, 3. 1999. [View Context].

Pedro Domingos. Knowledge Discovery Via Multiple Models. Intell. Data Anal, 2. 1998. [View Context].

Zhi-Hua Zhou and Xu-Ying Liu. Training Cost-Sensitive Neural Networks with Methods Addressing the Class Imbalance Problem. [View Context].

James J. Liu and James Tin and Yau Kwok. An Extended Genetic Rule Induction Algorithm. Department of Computer Science Wuhan University. [View Context].

Citation Request:

Please refer to the Machine Learning Repository's citation policy

[1] Papers were automatically harvested and associated with this data set, in collaboration with

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