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22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)
Thanks to the ubiquitous computing, the scale of data collection in various fields has been growing rapidly. Medicine is one of the fields that can benefit from the big data. However, it is faced with a big challenge because medical datasets are normally in high dimensions. Therefore, reducing dimensionality and finding the optimal set of features or attributes is of great importance. This paper presents...
Web attacks are increasing and the scale of malicious URL continues to expand with the rapid development of the Internet, so that the network security situation is increasingly grim. In this case, this paper studies the URL multi-classification problem, which is a continuation of the reference [1] and follows the data sets and most of feature selection methods in it. Firstly, different types of URL...
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...
A novel differential evolution algorithm is proposed for constrained optimization problems (COPs). The proposed algorithm combines the ideas between the self-adaptive differential evolution algorithm (JDE) and simple penalty function method (SPFM). Simulation results on the bump problem show that the solutions of the new algorithm is better than those of the algorithms in the almost exiting literature...
Image classification mainly uses the classifier to classify the extracted image features. In the traditional image feature extraction, it is difficult to set the appropriate feature patterns for the complex images. Simultaneously, the training algorithm of the classifier also affects the accuracy of image classification. In order to solve these problems, the combination of deep belief networks and...
Due to the imbalanced distribution of business data, missing of user features and many other reasons, directly using big data techniques on realistic business data tends to deviate from the business goals. It is difficult to model the insurance business data by classification algorithms like Logistic Regression and SVM etc. This paper exploits a heuristic bootstrap sampling approach combined with...
With the rapid development of Internet, we have entered an era of information explosion, there is a lot of redundant information in the Network. How to extract a useful part of this information from the massive information resources, analyzing the vast amount of information and finally get the potential knowledge we want to extract. Web mining technology came into being, and saved out the human from...
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