Classification of benign and malignant tumor cells using random tree and knn classifiers from Wisconsin dataset for the potential diagnostic application

• Published in: AIP conference proceedings Vol. 2816; no. 1
• Main Authors: Koyyala, Umakanth, Thirunavukkarasu, Usharani
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 22.03.2024
• Subjects: Classifiers; Data mining; Data systems; Datasets; Diagnostic software; K-nearest neighbors algorithm; Machine learning; Software; Statistical analysis; Tumors; United States > US; Wisconsin

Aim: The study’s goal is to categorise benign and malignant tumour cells from the Wisconsin dataset using Random tree and K-nearest neighbour classifiers for possible diagnostic applications. Materials and Methods: Breast cancer report and data system (WDBC) with benign (n=21) and malignant (n=21) m...