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This paper presents a Transductive Support Vector Machine (TSVM) with quasi-linear kernel based on a clustering assumption for semi-supervised classification. Since the potential separating boundary is located in low density area between classes, a modified density clustering method by considering label information is firstly introduced to extract the information of potential separating boundary in...
This paper proposes an improved SVM based multi-label classification method by using relationship among labels. Following a traditional multi-label solution, binary relevance (BR) method is first used to decompose the multi-label classification problem into multiple binary classification sub-problems, each of which is solved by an SVM classifier. By using Platt's sigmoid technique, each SVM classifier...
This paper presents a new strategy to build multi tree hierarchical structure SVM which can get a more efficient and accuracy classification model for multiclass problems. Base on the theory of Binary Tree SVM (BTS), we proposed an improvement algorithm which extend binary tree structure to a multi tree structure, In the multi tree hierarchical structure, similarity clustering method was proposed...
As the consistency prediction of data view in information systems and actual data, data quality is of vital importance to decision making and the development of banking industry. In this paper, we firstly analyze the influence of data quality on the banking industry, and make researches on the current situation of banking industry data quality automated management. Then five evaluation dimensions...
Software build system (e.g., Make) plays an important role in compiling human-readable source code into an executable program. One feature of build system such as make-based system is that it would use a build configuration file (e.g., Make file) to record the dependencies among different target and source code files. However, sometimes important dependencies would be missed in a build configuration...
We demonstrate through a pressure sensor matrix, that weight distribution on feet is influenced by body posture. A small cheap carpet equipped with low precision pressure sensor matrix is already sufficient to detect subtle activities and identity of the person on the carpet. By a 0.4 m2 matrix of 32 × 32, 12 bit pressure sensors, we achieve 78.7% accuracy for 11 test subjects performing 7 subtle...
Dynamometer cards are commonly used to analyze down-hole conditions of beam pumping units in practical oil production. In the literature, supervised learning based methods heavily rely on training samples. In order to realize unsupervised learning of fault diagnosis for down-hole conditions, a method based on an improved fuzzy Iterative Self-Organizing Data Analysis Technique (ISODATA) with “merging”...
QoS-aware service composition intends to maximize the global QoS of a composite service while selecting candidate services from different providers with local and global QoS constraints. With more and more candidate services emerging from all over the world, the network delays often greatly impact the performance of the composite service, which are usually not easy to be collected before the composition...
As we approach the era of exascale computing, the role of distributions to summarize, analyze and visualize large scale data is becoming more and more important. Since histograms continue to be a popular way of modeling the underlying data distribution, we propose a scalable and distributed framework for computing histograms from scalar and vector data at different levels of detail required by various...
The application of blind source separate (BSS) for forecasting the solar irradiance is presented. First, we used BSS method to separate the initial time sequence, and then we designed the best neural network topology. In consideration of the complex behavior of solar irradiance, either periodic or random, a kind of dynamic neural network, RBFN, was used for such case. After that the separating results...
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