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MACHINE LEARNINGType I error in hypothesis testing is (i) Accepting null when false (ii) Rejecting null when true (iii) Rejecting alternative when false (iv) Accepting alternative when true20252mArtificial intelligenceDescribe the following with suitable examples: Logistic regression20207mMACHINE LEARNINGQ.2 (b) Explain the inductive biased hypothesis space.20237mMACHINE LEARNINGA patient takes a lab test and the result comes back positive. It is known that the test returns a correct positive result in only 98% of the cases and a correct negative result in only 97% of the cases. Furthermore, only 0.008 of the entire population has this disease. (i) What is the probability that this patient has cancer? (ii) What is the probability that he does not have cancer? (iii) What is the diagnosis?20237m
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