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For solving the incomplete data problem of missing feature values in prototype data, various strategies were proposed. In this paper, two improved approaches are proposed to estimate the missing values of incomplete data. The two approaches are based on combining the adaptive volume Gustafson-Kessel algorithm (GKA) and the nearest vector features under the distance norm evaluated by complete data...
A fuzzy classifier with adaptive learning of the volume of norm inducing matrix is proposed in this paper. The proposed fuzzy classifier improves the Gustafson-Kessel algorithm (GKA) which assumes a fixed volume of the norm inducing matrix. An efficient approach based on gradient descent learning, called adaptive ellipsoid classification algorithm (AECA) is proposed to recursively update the volume...
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