  The MobileNet model was used by applying transfer learning on the 7 skin
diseases to create a skin disease classification system on Android application.
The proponents gathered a total of 3,406 images and it is considered as
imbalanced dataset because of the unequal number of images on its classes.
Using different sampling method and preprocessing of input data was explored to
further improved the accuracy of the MobileNet. Using under-sampling method and
the default preprocessing of input data achieved an 84.28% accuracy. While,
using imbalanced dataset and default preprocessing of input data achieved a
93.6% accuracy. Then, researchers explored oversampling the dataset and the
model attained a 91.8% accuracy. Lastly, by using oversampling technique and
data augmentation on preprocessing the input data provide a 94.4% accuracy and
this model was deployed on the developed Android application.
