What is the difference between type I vs type II error?

Data Science, AI and ML
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#1

What is the difference between type I vs type II error?

#2

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.
ref:https://medium.com/acing-ai/what-is-better-a-type-i-or-a-type-ii-error-960f7d1799df