DS-200 Question #62: Real Exam Question with Answer & Explanation

There are 20 patients with acute lymphoblastic leukemia (ALL) and 32 patients with acute myeloid leukemia (AML), both variants of a blood cancer. The makeup of the groups as follows: Each individual has an expression value for each of 10000 different genes. The expression value for each gene is a continuous value between -1 and 1. You've built your model for discriminating between AML and ALL patients and you find that it works quite well on your current data. One month later, a collaboration tells you she has fresh data from 100 new AML/ALL patients. You run the samples through your model, and turns out your model has very poor predictive accuracy on the new samples; specifically, your model predicts that all males have ALL. What is the most reliable way to fix this problem?