Black box versus not

For the sake of efficiency, we did not examine the classification algorithms used very closely. When we compared SVC and logistic regression, we chose SVMs. At that point, both algorithms were black boxes, as we did not know any internal details. Once we decided to focus on SVMs, we could proceed to compute coefficients of the separating hyperplanes involved, optimize the hyperparameters of the SVM, use the SVM for big data, and do other processes. The SVMs have earned our time investment because of their superior performance.