BIOMEDICAL TEXT DOCUMENT CLASSIFICATION

Information extraction, retrieval, and text categorization are only a few of the significant research fields covered by "bio medical classification." This study examines many techniques utilised in practise, as well their strengths weaknesses, order to improve knowledge various information extraction opportunities field data mining. We compiled dataset with focus on three categories: "Thyroid Cancer," "Lung "Colon Cancer." paper presents an empirical classifier. The investigation was carried out using biomedical literature benchmarks. Many metaheuristic algorithms investigated, including genetic algorithms, particle swarm optimisation, firefly, cuckoo, bat algorithms. In addition, proposed multiple classifier system outperforms ensemble learning, pruning, traditional classification methods. Based data, we forecast if it is Thyroid Cancer, Lung or Colon Cancer basic EDA, preprocessing, several models such Logistic Regression, Decision Tree Classification, Random Forest Classification.