  This manuscript briefly describes an algorithm developed for the ISIC 2017
Skin Lesion Classification Competition. In this task, participants are asked to
complete two independent binary image classification tasks that involve three
unique diagnoses of skin lesions (melanoma, nevus, and seborrheic keratosis).
In the first binary classification task, participants are asked to distinguish
between (a) melanoma and (b) nevus and seborrheic keratosis. In the second
binary classification task, participants are asked to distinguish between (a)
seborrheic keratosis and (b) nevus and melanoma. The other phases of the
competition are not considered. Our proposed algorithm consists of three steps:
preprocessing, classification using VGG-NET and Random Forests, and calculation
of a final score.
