In the first phase, a fuzzy support vector machine is proposed for the classification of real-world data with noise, fuzzy membership to each data point of SVM ...
Support vector machine is learning system that uses a hypothesis space of linear function in high dimensional feature space[1], which has been recently ...
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Oct 22, 2024 · In this paper, we apply a fuzzy membership to each input point and reformulate the SVMs such that different input points can make different constributions.
This paper proposes an effective personalizing method using small-sized local data. The proposed method utilizes a fuzzy support vector machine to allocate ...
In this paper, to overcome this problem, we propose fuzzy support vector machines (FSVMs). Using the decision functions obtained by training the SVM, for each ...
In the first phase, a fuzzy support vector machine is proposed for the classification of real-world data with noise, fuzzy membership to each data point of SVM ...
A fuzzy classifier based on Support Vector Machine (FCBSVM) was proposed. The basic idea and the structure of this classifier were introduced.
Sep 2, 2019 · Fuzzy SVMs (FSVMs) is a variant of the SVM algorithm, which has been proposed to handle the problem of outliers and noise. In FSVMs, training ...
Feb 11, 2014 · Fuzzy support vector machine model for classification problems. In this section we briefly review the basic theory of SVM for classification.
A new fuzzy support vector machine algorithm based on SVDD is presented in this paper. In our algorithm, the noises and outliers are identified by a ...