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Annealing Data Set Download: Data Folder, Data Set Description Abstract: Steel annealing data |
Data Set Characteristics: | Multivariate | Number of Instances: | 798 | Area: | Physical
Attribute Characteristics: | Categorical, Integer, Real | Number of Attributes: | 38 | Date Donated | N/A
Associated Tasks: | Classification | Missing Values? | Yes | Number of Web Hits: | 34839
Source: Donors: David Sterling and Wray Buntine Data Set Information: N/A 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: N/A 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 Rexa.info

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