Development of a Model to Classify Skin Diseases using Ensemble Machine Learning Techniques

Skin diseases are highly prevalent and transmissible in Africa. A patient can be cured from these skin diseases if it is detected on time and treated at an early stage. However, it is difficult to identify these diseases in order to provide the right medications. This work presents an ensemble technique of five machine learning models to improve the accuracy level of classifying skin diseases. The result showed that the stacking method yield a high accuracy of 99.30% compared to the single classifiers and existing works.