I am currently doing my master's thesis and at the end of finishing it, but there are some questions raised by my supervisor. I have answered most of the questions, but only one question is remaining and I don't know how to answer it.
I am doing my master thesis on classifying the given medical data into Cancer or Immune, and the visualization of data points after preprocessing looks like the below image,
Now, I have used SVM with kernels, Decision Trees, and Random Forests algorithms to classify the data points and they yield a very good accuracy and F1 score, but my supervisor is asking the following question
I can nearly perfectly classify this data by drawing three vertical lines. Instead, very complicated decision trees are provided. It should be discussed why it is not appropriate to draw such three vertical lines, or if it is, why the algorithms do not find them. The quality of the classifiers according to the decision trees should be compared with the simple method I propose.
So could you please share your knowledge on this question and help me?