Results 241 to 250 of about 707,669 (303)
Multimedia Tools and Applications, 2016 Feature extraction is an essential task in the classification of high-resolution remote sensing images, with the primary technique being the object-oriented classification method. Current research describes object-oriented classification methods by using remote sensing data, wherein how to reduce the redundant feature information to achieve good ...
Yi Zeng +3 more
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An Intelligent Stock-Selecting System Based on Decision Tree Combining Rough Sets Theory
, 2013 This study presents a stock selective system by using hybrid models to look for sound financial companies that are really worth making investment in stock markets. The following are three main steps in this study: First, we utilize rough sets theory to sift out the core of the financial indicators affecting the ups and downs of a stock price.
Shou-Hsiung Cheng
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A New Method for Constructing Decision Tree Based on Rough Set Theory
IEEE International Conference on Granular Computing, 2007 Longjun Huang +3 more
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<title>Application of preprocessing filtering on Decision Tree C4.5 and rough set theory</title>
SPIE Proceedings, 2001 This paper compares two artificial intelligence methods: the Decision Tree C4.5 and Rough Set Theory on the stock market data. The Decision Tree C4.5 is reviewed with the Rough Set Theory. An enhanced window application is developed to facilitate the pre-processing filtering by introducing the feature (attribute) transformations, which allows users to ...
Joseph C. C. Chan, Tsau Young Lin
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Fuzzy integrated rough set theory situation feature extraction of network security
Journal of Intelligent & Fuzzy Systems, 2021The element extraction from network security condition is the foundation security awareness. Its excellence directly disturbsentire security system performance.
Dongmei Zhao, Huiqian Song, Hong Li
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Parameter trees based on soft set theory and their similarity measures
Soft Computing, 2022 Faruk Karaaslan, Naim Çağman
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Construction of Decision Tree Based on Rough Sets Theory
Advanced Materials Research, 2012In the process of constructing decision trees, the selecting criteria of classification attributes will directly affect the classification results. Here we presented the classification contribution function (CCF), a new concept based on rough sets theory, which is regarded as the criteria for choosing attributes in the core of attributes.
Lin Li Wu, Zhi Jun Lei
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An Integration of Cloud Transform and Rough Set Theory to Induction of Decision Trees
Fundamenta Informaticae, 2009Decision trees are one of the most popular data-mining techniques for knowledge discovery. Many approaches for induction of decision trees often deal with the continuous data and missing values in information systems. However, they do not perform well in real situations.
Da Ruan, Jing Song, Tianrui Li
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A fast algorithm for attribute reduction based on Trie tree and rough set theory
SPIE Proceedings, 2013Attribute reduction is an important issue in rough set theory. Many efficient algorithms have been proposed, however, few of them can process huge data sets quickly. In this paper, combining the Trie tree, the algorithms for computing positive region of decision table are proposed.
Xiao Yan Wang +3 more
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An approximately unbiased test of phylogenetic tree selection.
Systematic Biology, 2002An approximately unbiased (AU) test that uses a newly devised multiscale bootstrap technique was developed for general hypothesis testing of regions in an attempt to reduce test bias.
Hidetoshi Shimodaira
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