Data Fusion in Radial Basis Function Networks for Spatial Regression
Neural Processing Letters
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The study proposes a modified RBF with better network learning, convergence, error rates and classification results which involves spatial information data points using Gaussian Mixture Model (GMM) and Expectation Maximization (EM) algorithm for automatic biomedical brain tumour detection. The model was used to predict the brain tumour type (benign or malignant). The results showed outperformance of GMM-EM model with spatial points than the standard RBF model.A classification with a success of 85% and 90.3% has been obtained by the classifiers for RBF and RBF-GMM model.