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Feature representation plays an important role in text classification. Feature mapping based on labels information is an algorithm suitable for Binary Relevance. Compared with the conventional text representation, it makes the dimension of the text under control by means of word embedding. More importantly, it takes full advantage of the general characteristics of the label on text representation...
In this paper, we analyze the fundamental principles, and pros and cons of ICA and SVM, which are commonly used for face recognition. After investigating the SVM-based multiclass classification algorithm, we propose an improved binary tree SVM method, which is then combined with ICA to recognize faces. Features are first extracted via ICA in the experiment on the ORL face dataset. The improved binary...
The protocol identify of space unknown protocol data can use the method of SVM, but before the identify must have a large number of study data for the process of training. This paper proposes a new space transfer data classification algorithm PCC which can class the unknown protocol space data as different sorts. The PCC arithmetic include three processes of relationship of different layer protocol,...
Allusion to the various different requirements QoS's quota such as delay sensitivity of multi-medium business for Multi-media communication in Heterogeneous wireless network, we put forward the attemper arithmetic of classify queue based on multi-medium communication. Grade the now operation according to the factors of flux, delay and error tolerance etc, and the node that participates transmission...
Decision tree induction is an important way of learning rules from examples. Due to the NP-hard problem, heuristic algorithms play a crucial role for generating short decision trees. This paper investigates the comparison between two heuristic algorithms in decision tree generation for the capacity of resisting noise. One heuristic is the well-known ID3 while the other is our previously proposed....
To help handle battlefield information superiority to decision superiority (i.e. to rapidly arrive at better decisions than adversaries can respond to), many scientific, technical and technological challenges must be addressed. The most critical of those are information fusion and management at different levels, communication. This paper decribes battlefield information as data streams and mining...
Mining concept drifting data stream is a challenging area for data mining research. Recent years have witnessed an averaging ensemble classifier which is based on the learnable assumption, although this ensemble classifier is an efficient algorithm for mining concept-drifting data streams, it is still inadequate to represent real-world data streams with noisy data. In this paper, we propose a novel...
This paper focuses on continuous attributes handling for mining data stream with concept drift. Data stream is an incremental, online and real time model. Domingos and Hulten have presented a one-pass algorithm. Their system VFDT use Hoeffding inequality to achieve a probabilistic bound on the accuracy of the tree constructed. VFDTpsilas extended version CVFDT handles concept drift efficiently. In...
Through the analysis of the information on the contents of the document which contained in title, abstract and keywords, find out which documents are more relativity with user's retrieval expectation, this paper adopted "document retrieval expected value" as be the indicator, builds the mathematical model for it, and then takes advantage of it to do the quantitative calculation for all documents...
In many real world data mining and classification tasks, we face with the problem of high cost in making training data sets. In addition, in many domains, different misclassification errors involve different costs. These two issues are often addressed by semi-supervised learning and cost-sensitive learning separately. Sometimes the two issues can happen at the same time in real world applications...
Emerging video-mining applications such as image and video retrieval and indexing will require real-time processing capabilities. A many-core architecture with 64 small, in-order, general-purpose cores as the accelerator can help meet the necessary performance goals and requirements. The key video-mining modules can achieve parallel speedups of 19times to 62times from 64 cores and get an extra 2.3times...
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