Cancer Classification using Adaptive Neuro Fuzzy Inference System with Runge Kutta Learning

Abstract

Cancer research is one of the major research areas in the medical field. Adaptive Neuro Fuzzy Interference System is used for the classification of Cancer. This algorithm compared with proposed algorithm of Adaptive Neuro Fuzzy Interference system with Runge Kutta learning method for the best classification of cancer. It is one of the better techniques for the classification of the cancer. The Adaptive Network-based Fuzzy Inference System is one of the well-known neural fuzzy controllers with fuzzy inference capability. For the cancer classification inputs are collected from the dataset of Lymphoma dataset and Leukemia dataset. In this paper, focused in classification of cancer by using ANFIS with RKLM. Keywords ANFIS, RKLM, ANFIS with RKLM.