Dermatological disease is common in places that are humid, damp, and hot like Taiwan, various reasons can cause skin diseases with which the symptoms are varied. This study has mainly focusing on six major types of skin diseases which the actual data of the skin condition were feature transformed and were then classified by using SVM to build a new prediction model for dermatology. The support vector machine (SVM) classifier is a popular and appealing classifier. It could be improved by taking some transformation about the original data before classification even sometimes its performance is not good. In this paper, two transformations are considered. One is the well known transformation, NWFE-Transformation and the other is a novel transformation, Liu-Transformation proposed by our previous work. For evaluating the performances of the SVM without any transformation, the SVM with the NWFE-Transformation and the SVM with the Liu-Transformation, a real data experiment by using 5-fold 10-fold and Leave-one-out Cross-Validation accuracy is conducted. Experimental result shows that the SVM with the proposed Liu-Transformation algorithm has the best performance. The study is conducted in the hope that the AI classification technology can serve as useful references for physicians and patients in the diagnose of the skin diseases to avoid unnecessary medical expenses and to enhance health care quality.
