Results 21 to 30 of about 28,526 (253)
Sliding Block-Based Hybrid Feature Subset Selection in Network Traffic
IEEE Access, 2017 Traffic classification is currently a significant challenge for network monitoring and management. Feature selection is an effective method to realize dimension reduction and decrease redundant information.
Jian Shen +3 more
doaj +1 more source
Incremental Subgraph Feature Selection for Graph Classification
IEEE Transactions on Knowledge and Data Engineering, 2017 Graph classification is an important tool for analyzing data with structure dependency, where subgraphs are often used as features for learning. In reality, the dimension of the subgraphs crucially depends on the threshold setting of the frequency support parameter, and the number may become extremely large.
Haishuai Wang +6 more
openaire +1 more source
Frontiers in Cell and Developmental Biology, 2021 The 2-oxoglutarate/Fe (II)-dependent (2OG) oxygenase superfamily is mainly responsible for protein modification, nucleic acid repair and/or modification, and fatty acid metabolism and plays important roles in cancer, cardiovascular disease, and other ...
Jian Zhou +5 more
doaj +1 more source
Dynamic Fuzzy Rough Feature Selection Algorithm
Jisuanji kexue yu tansuo, 2020 Since data update over time and space constantly, many rough set based incremental techniques have been proposed. Whereas there is less work on fuzzy rough set based feature selection (i.e., attribute reduction) from the dynamic data, especially the ...
NI Peng, LIU Yangming, ZHAO Suyun, CHEN Hong, LI Cuiping
doaj +1 more source
Metric Based Attribute Reduction Method in Dynamic Decision Tables
Cybernetics and Information Technologies, 2016 Feature selection is a vital problem which needs to be effectively solved in knowledge discovery in databases and pattern recognition due to two basic reasons: minimizing costs and accurately classifying data.
Janos Demetrovics +3 more
doaj +1 more source
Transfer Incremental Learning Using Data Augmentation
Applied Sciences, 2018 Deep learning-based methods have reached state of the art performances, relying on a large quantity of available data and computational power. Such methods still remain highly inappropriate when facing a major open machine learning problem, which ...
Ghouthi Boukli Hacene +4 more
doaj +1 more source
Functional and embedding feature analysis for pan-cancer classification
Frontiers in Oncology, 2022 With the increasing number of people suffering from cancer, this illness has become a major health problem worldwide. Exploring the biological functions and signaling pathways of carcinogenesis is essential for cancer detection and research.
Jian Lu +8 more
doaj +1 more source
Improved incremental algorithm of Naive Bayes
Tongxin xuebao, 2016 A novel Naive Bayes incremental algorithm was proposed,which could select new features.For the incremental sample selection of the unlabeled corpus,a minimum posterior probability was designed as the double threshold of sample selection by using the ...
Shui-fei ZENG +3 more
doaj +2 more sources
Frontiers in Genetics, 2020 BackgroundPancreatic ductal adenocarcinoma (PDAC) is the most aggressive form of pancreatic cancer. Its 5-year survival rate is only 3–5%. Perineural invasion (PNI) is a process of cancer cells invading the surrounding nerves and perineural spaces. It is
Jin-Hui Zhu +6 more
doaj +1 more source
Dimension Incremental Feature Selection Approach for Vertex Cover of Hypergraph Using Rough Sets
IEEE Access, 2018 The minimum vertex cover problem is a well-known optimization problem; it has been used in a wide variety of applications. This paper focuses on rough set-based approach for the minimum vertex cover problem of the dynamic and static hypergraphs.
Qian Zhou, Xiaolin Qin, Xiaojun Xie
doaj +1 more source