(1995): StatLog: Comparison of Classification Algorithms on Large Real-World Problems. Applied Artificial Intelligence, 9(3), 289-333.King, R.D., Feng, C., and Sutherland, A., Statlog: comparison of classification algorithms on large real-world problems, Applied Artificial Intelligence, 9:289...
Using a total of 7 large Illumina Infinium 27k Methylation data sets, encompassing over 1,000 samples from a wide range of tissues, we here provide an evaluation of popular feature selection, dimensional reduction and classification methods on DNA methylation data. Specifically, we evaluate the eff...
[Lecture Notes in Electrical Engineering] Computational Science and Technology Volume 481 (5th ICCST 2018, Kota Kinabalu, Malaysia, 29-30 August 2018) || Comparison of Classification Algorithms on ICMPv6-Based DDoS Attacks Detection 来自 onAcademic 喜欢 0 阅读量: 33 ...
Network noise is one of the most challenging issues for efficient threat detection and classification. In this study, normal and noisy datasets for network IDS domain are used and various classification algorithms are evaluated. The results show that an evaluation of algorithms without noise is ...
Subsequently, the classification algorithm that has the optimal potential will be suggested for use in large scale data.Kittipol WisaengSeventh Sense Research Group JournalInternational Journal of Engineering Trends & TechnologyWisaeng, K. A comparison of decision tree algorithms for UCI repository ...
There are three key issues about online classification: observation window size, feature selection, and classification algorithms.In this paper, by collecting five types of typical network flow data as the experiment sample data, the authorsfound observation window size 7 is the best for the sample...
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline decodin
The overall performance of RF and SVM (linear kernel) is superior to the others. Some selected variables are of significance for further research on metabolic difference. 展开 关键词: support vector machine classification metabolic profiling random forest ...
Learning Algorithms for Classification: A . . . This paper compares the performance of several classifier algorithms on a standard database of handwritten digits. We consider not only raw accuracy, but also training time, recognition time, and memory requirements. When available, we r... Y Le...
of compositional bias yields at least as sensitive and much more specific results. Besides the application of sequence masking algorithms to sequence similarity searches, the study of the masked regions themselves is of great interest. Traditionally, however, these have been neglected despite evidence ...