hybSVM: Bacterial colony optimization algorithm based SVM for malignant melanoma detection
Sümeyya İlkin, Tuğrul Hakan Gençtürk, Fidan Kaya Gülağız, Hikmetcan Özcan, Mehmet Ali Altuncu, Suhap Şahın
Abstract
Melanoma is a malignant and aggressive type of skin cancer. This paper describes an effective method for detection of melanoma. A hybrid classification algorithm was developed by using the SVM algorithm and a heuristic optimization algorithm. In this algorithm, the SVM algorithm which uses a Gaussian Radial Basis Function (RBF) was enhanced by the Bacterial Colony algorithm (hybSVM). The model was tested with two different datasets namely ISIC and PH2 by using 10 cross fold validation. According to results AUC value of 98%, 97% and an operation time of 26.5, 11.9 sec obtained respectively from ISIC and PH2.
Topics & Concepts
Support vector machineComputer scienceAlgorithmArtificial intelligenceMelanomaPattern recognition (psychology)MedicineCancer researchCutaneous Melanoma Detection and ManagementAI in cancer detectionCell Image Analysis Techniques