Extended semi-supervised fuzzy learning method for nonlinear outliers via pattern discovery
A parameterized fuzzy LDA is proposed as semi-supervised learning precursor. Apply Hopfield Neural Network to dynamic parameter estimation. Separate outlier instances from the whole feature space. Obtain the initial fuzzy classification of regular feature space. Semi-supervised fuzzy clustering algorithm is presented on the basis of class discriminatory measure for the nonlinear outliers.
parameter estimation outlier instances fuzzy discriminant analysis semi-supervised clustering image recognition