Question: what is type 1 and type 2 error in machine learning?
Answer: Type I error is equivalent to a False positive. Type II error is equivalent to a False negative. Type I error refers to non-acceptance of hypothesis which ought to be accepted. Type II error is the acceptance of hypothesis which ought to be rejected.