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Physical location is an important characteristic for digital individuals, as it is widely used in location based services, such as navigation, advertisements, and recommendations. This paper focuses on the problem of inferring individual physical locations from their friendships in a social network. We represent individual locations with a few high frequency places to eliminate the noise influence...
Support vector machine is effective method for resolving non-liner classification and regression problem, but it is sensitive to the noises and outliers in the training samples. In order to overcome this problem, fuzzy support vector machine (FSVM) is introduced. How to choose a proper fuzzy membership is very important for the practical problem in FSVM. Generally, fuzzy membership is built according...
In this paper, an improved fuzzy membership function determination is proposed to train the fuzzy support vector machine (FSVM) for classification which the sample set in reality environment is increasing, and it often contains a lot of noise and outliers. In the improved algorithm, the sample points have the different types of memberships in different regions. The dual membership is introduced to...
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