@sid100158 wrote:
I am currently solving one classification problem using logistic regression.I want to know how we can calculate baseline prediction in a classification problem just like we can find baseline prediction in a linear regression by finding the average dependent variable.
I have data in which I have to predict quality of health care . quality=read.csv("quality.csv") str(quality) 'data.frame': 131 obs. of 14 variables: $ MemberID : int 1 2 3 4 5 6 7 8 9 10 ... $ InpatientDays : int 0 1 0 0 8 2 16 2 2 4 ... $ ERVisits : int 0 1 0 1 2 0 1 0 1 2 ... $ OfficeVisits : int 18 6 5 19 19 9 8 8 4 0 ... $ Narcotics : int 1 1 3 0 3 2 1 0 3 2 ... $ DaysSinceLastERVisit: num 731 411 731 158 449 ... $ Pain : int 10 0 10 34 10 6 4 5 5 2 ... $ TotalVisits : int 18 8 5 20 29 11 25 10 7 6 ... $ ProviderCount : int 21 27 16 14 24 40 19 11 28 21 ... $ MedicalClaims : int 93 19 27 59 51 53 40 28 20 17 ... $ ClaimLines : int 222 115 148 242 204 156 261 87 98 66 ... $ StartedOnCombination: logi FALSE FALSE FALSE FALSE FALSE FALSE ... $ AcuteDrugGapSmall : int 0 1 5 0 0 4 0 0 0 0 ... $ PoorCare : int 0 0 0 0 0 1 0 0 1 0 ... table(quality$PoorCare) 0 1 98 33In this data I want to know the baseline prediction of PoorCare.
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