GitHub - javachip8786/Skin_Cancer_Detection: Using 2 datasets, one with 4000 images( 2000 bengin and 2000 Malignant) and apply Pre-processing steps Dull razor(to remove hairs), Median filtering, Otsu Algorithm and Chanvese Algorithm and then performing Exploratory data analysis after which we extract 7 features from those images which we use for training our model, here we apply many models such as logistic regress, Random forest, KNN and also ensembling techniques which gives us a maximum accuracy of 77. The second data is Already of the internet with 3661 rows and 80 features on which we applied CNN with cross entropy loss and it gave us state of the art Accuracy 97.13% which is even higher than 96%(Authors accuracy).

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Using 2 datasets, one with 4000 images( 2000 bengin and 2000 Malignant) and apply Pre-processing steps Dull razor(to remove hairs), Median filtering, Otsu Algorithm and Chanvese Algorithm and then performing Exploratory data analysis after which we extract 7 features from those images which we use for training our model, here we apply many model…