Your question is Imbalanced Rare Symbol Learning. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you handle highly imbalanced datasets where the target feature, such as a rare architectural symbol, appears in less than 1% of your training data for Plangrid?