HFCVO-DMN: Henry Fuzzy Competitive Verse Optimizer-Integrated Deep Maxout Network for Incremental Text Classification

One of the effectual text classification approaches for learning extensive information is incremental learning. The big issue that occurs enhancing accuracy, as comprised a large number terms. In order to address this issue, new approach designed using proposed hybrid optimization algorithm named Henry Fuzzy Competitive Multi-verse Optimizer (HFCVO)-based Deep Maxout Network (DMN). Here, optimal features are selected Invasive Weed Tunicate Swarm Optimization (IWTSO), which devised by integrating (IWO) and Algorithm (TSA), respectively. effectively performed DMN, where classifier trained utilizing HFCVO. Nevertheless, developed HFCVO derived incorporating Gas Solubility (HGSO) (CMVO) with fuzzy theory. HFCVO-based DNM achieved maximum TPR 0.968, TNR 0.941, low FNR 0.032, high precision 0.954, accuracy 0.955.