Figure 6
Classification performance (accuracy) for Random Forest and Support Vector Machine. Input for Random Forest (RF; a) and Support Vector Machine (SVM; b) consisted of global statistical parameters extracted from images generated using each of the 5 filters for each of the 3 dog groups (healthy [Golden Retriever; GR], dystrophic [Golden Retriever Muscular Dystrophy; GRMD] and MuStem cell-treated dystrophic GRMD [GRMDT] dogs) and those extracted from all 5 filters combined. (c) Performance classification data obtained for the RF and SVM approaches using as inputs the combination of global and complementary local statistical parameters calculated only for images captured using filter 4 of the 3 dog classes. In both instances (default and optimized parameters), a k-fold cross validation was applied using k = 10. Bars representing standard deviation are shown only for the optimized RF and SVM conditions, as in all the other cases these values were very small (< 0.01%).
