By Xizhao Wang, Witold Pedrycz, Patrick Chan, Qiang He
This e-book constitutes the refereed court cases of the thirteenth overseas convention on computer studying and Cybernetics, Lanzhou, China, in July 2014. The forty five revised complete papers provided have been conscientiously reviewed and chosen from 421 submissions. The papers are geared up in topical sections on class and semi-supervised studying; clustering and kernel; software to reputation; sampling and massive information; software to detection; selection tree studying; studying and model; similarity and determination making; studying with uncertainty; stronger studying algorithms and applications.
Read or Download Machine Learning and Cybernetics: 13th International Conference, Lanzhou, China, July 13-16, 2014. Proceedings PDF
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Additional info for Machine Learning and Cybernetics: 13th International Conference, Lanzhou, China, July 13-16, 2014. Proceedings
Example text
It identifies object with the same attribute or the same function which would be more beneficial for mining important information. In this paper, the proposed method adopts a new CAD framework for the classification of breast cancers as benign or malignant. Methods for grading the input image data under features recommended by the sonographic BI-RADS lexicons [12] and biclustering grades using the prior label information for mining diagnostic patterns are proposed. Finally, the k-NN classifier is applied to perform classification of tumor types.
In [17] applied the ordinal classification technique to text information mining and obtained a promising performance. From the literature we do not find a study on the extension of SOCA by considering the ordering information of conditional attributes, aiming at an improvement of accuracy for ordinal classification. In this paper, we make an attempt to conduct such an improvement. By considering the ordering information both in conditional attributes and decision attribute, we develop an improved model of ordinal classification SOCA.
Michigan, pp. 115–124 (2005) 12. : Exploring in the weblog space by detecting informative and affective articles. In: Proceedings of the 16th International Conference on World Wide Web, pp. 281–290. ACM (2007) 13. : MMSEG: a word identification system for mandarin Chinese text based on two variants of the maximum matching algorithm (2000). com/hao150/ mmseg/ 14. : Tmsvm Reference Documents. docx Accessed: (May 1, 2013) (in Chinese) 15. : A Comparative Study on Feature Selection in Text Categorization.