Predictive Analysis for Cancer and Diabetes Using Simplex Method Based Social Spider Optimization Algorithm.

Early stage of prediction and diagnosis is the only way to solve the challenges due to medical data. Machine learning tools and techniques help in prediction and diagnosis of different types of medical data. In this paper, Simplex Method based Social Spider Optimization (SMSSO) method is used which modifies the Social Spider Optimization (SSO) method. Different types of datasets were used to validate the SMSSO-NN technique. SMSSO-NN shows 99.36%, 94%, 95.78%, and 98% accuracy in Wisconsin Breast Cancer (WBC), Lung cancer, Diabetic, and Cervical cancer datasets, respectively that is better than other methods. The accuracy of the SMSSO-NN algorithm is associated with different classification techniques like Structured Singular Value (SSV), Local Linear Wavelet Neural Network-Firefly Algorithm (LLWNN-FA), and Rough Set Theory. [ABSTRACT FROM AUTHOR]