Abstract
The main aim of the study is to improve the prediction rate in fake news detection. A novel Learning Vector Quantization (LVQ) with hamming distance is proposed for effective prediction of fake news. The sample size is calculated as N=10 for multi group analysis using the G-Power calculator. ISOT dataset is used for the study and the proposed learning vector quantization algorithm is executed and compared with three existing algorithms: Passive Aggressive classifier, LSTM and LS-SVM algorithm.
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