Skin Cancer Classification Using Random Forest Algorithm

Skin cancer is an excessive lump of skin tissue that affects the skin, has irregular structure with cell differentiation at various levels in chromatin, nucleus and cytoplasm, expansive, infiltrative to damage surrounding tissue, metastasizes through blood vessels lymph vessels. Diagnosis by biopsy process considered less effective because it costs a lot can injure human as sample. For that, we need system for classification types are accurate. The application machine learning been widely used health sector. One methods Random Forest. In this study, histogram color feature extraction will be carried out, hue moment shape extraction, haralick texture extraction. Furthermore, image classified using Forest algorithm. best accuracy value obtained from 0.850822. novelty research use more diverse better results than previous studies. Future expected deep algorithms CNN (Convolutional Neural Network) architecture get add designs models have formed study so they directly applied medical team.