Biomedical Text Categorization Based on Ensemble Pruning and Optimized Topic Modelling

<table class="fixed-width table-group" id="tab3"><tr><td><table class="table"><colgroup><col style="width:12.42em"/><col style="width:34.72em"/></colgroup><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Metaheuristic algorithm</td><td class="align_center">Parameter Values</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Genetic algorithms</td><td class="align_center">Crossover probability: 0.6, The number of generations to evaluate: 20, Mutation probability: 0.033, Population size: 20, Seed: 1</td></tr><tr><td class="align_left" colspan="2"><hr/></td></tr><tr><td class="align_left">Particle swarm optimization</td><td class="align_center">Individual weight: 0.34, Inertia weight: 0.33, Number of iterations: 20, Mutation probability: 0.01, Mutation type: bit-flip, Population size: 20, Seed: 1, Social Weight: 0.33</td></tr><tr><td class="align_left" colspan="2"><hr/></td></tr><tr><td class="align_left">Firefly algorithm</td><td class="align_center">α= 0.8, γ= 0.5, δ=0.85</td></tr><tr><td class="align_left" colspan="2"><hr/></td></tr><tr><td class="align_left">Cuckoo search algorithm</td><td class="align_center">Pa= 0.5</td></tr><tr><td class="align_left" colspan="2"><hr/></td></tr><tr><td class="align_left">Bat algorithm</td><td class="align_center">Ld=0.4, pr=0.4, fqmin=0, fqmax=2</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Parameters of the metaheuristics algorithms utilized in swarm-based LDA.</div>

Computational and Mathematical Methods in Medicine

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Table 3

Table 3: Biomedical Text Categorization Based on Ensemble Pruning and Optimized Topic Modelling 