Skin Cancer Prediction using Enhanced Genetic Algorithm with Extreme Learning Machine

In the current scenario, death rate due to cause of skin cancer is increasing enormously. Diagnosis and prediction Skin Cancer (SC) have become vital at an earlier stage. The main objective this research ensemble machine learning with enhanced genetic algorithm technique achieve higher accuracy in stage compared other existing techniques. Although many deep approaches implemented detecting still there are few limitations. To overcome these problems our proposed work, CNN model, ResNet-16 usually produces successful results extracting features automatically classifying images very accurately. Therefore, ResNet model used work obtains help a fully connected layer. Later feature selection performed Enhanced Genetic Algorithm (EGA) that optimized solutions by implementing operations like mutations, crossover, Extreme Learning Machine (EGA-ELM) classify as either melanoma or non-melanoma. certainly achieved effective performance. Finally, obtained be popular algorithms Support Vector (SVM) various models.