Construct a Decision Tree Model that predicts the diabetes patients based on the Polyuria,
Gender, Polydipsia, dan Alopecia elements. Show the steps and suitable R codes for each
step. i need the answer ASAP
Construct A Decision Tree Model That Predicts The Diabetes Patients Based On The Polyuria Gender Polydipsia Dan Alope 1 (60.63 KiB) Viewed 32 times
Given the diabetes patient dataset in Figure 3 and the description of each element in each row in Figure 4. Construct a Decision Tree Model that predicts the diabetes patients based on the Polyuria, Gender, Polydipsia, dan Alopecia elements. Show the steps and suitable R codes for each step. (8 markah/marks) flextable(head(df))%>% fontsize(size = 7, part = "all") sudden Age Gender Polyurta Polydipsia weight weakness Polyphagia loss 40 Male No 58 Male 41 Male 45 Male 60 Male 55 Male No Yes No Yes summary (df) ** Yes Age No No Yes Yes Yes No Min. :16.00 ## 1st Qu. :39.00 ## Median :47.50 Mean :48.03 ## 3rd Qu.:57.00 # Max. :90.00 ** No No No Yes No Yes #sudden weight loss ## Length: 520 ## Class : character ## Mode :character ## Yes Yes Yes Yes Yes No No Yes Yes Yes Genital visual thrush burring No No No Gender Length: 520 Class :character Mode :character No Yes Yes No No Yes No weakness Length: 520 Class :character Mode :character ching Irritabay Yes No No No Yes No Yes No Yes Ves Yes No delayed partial muscle healing paresis illness Yes No Yes You Rajah 3 Set Data Diabetes Figure 3 Diabetes Data Set Yes Yes Polyuria Length: 520 Class : character Mode :character No Yes No Yes No Polyphagia Length: 520 Class :character Mode :character Yes No Yes No Yes No Yes Alopecia Obesity class Yes Yes Yes No Yes Yes Yes No No No Yes Yes Polydipsia Length: 520 Class :character Mode :character Positive Positive Positive Positive Positive Positive Genital thrush Length: 520 Class :character Mode :character
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