For decision tree algorithms, if it classifies 100% data accurately, what do I do to somehow incorporate boosted tree algorithms into the code?

I am classifying metal defects using decision tree algorithms. When I input the code, it classifies 100% data accurately without any errors. It is only possible to incorporate boosted decision tree algorithms into the code only if the decision tree does not classify accurately. What do I do to include decision tree boost?

I have tried taking different vectors in the data in the CrossTable function and tried but all other vectors gave error in results expect for the vector ‘defect_type’ which is a character type vector. All the other vectors are numeric.