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Please write Python codes using “pima-indian-diabetes” data sets as attached with this question.

Goal: In this question, you will implement Logistic Regression, Regularized
(L2) Logistic Regression. The goal of
this question is to give you
experience in implementation of Logistic
Regression and analyze the
hyperparameter tuning in case of Regularized Logistic Regression.

Data sets:
The dataset that you use in this project is “pima-indians-diabetes”. Please find the attachments.

This dataset describes the medical records for Pima Indians and whether or not each
patient will have an onset of diabetes within year.

Fields description follow:
preg = Number of times pregnant
plas = Plasma glucose concentration a 2 hours in an oral glucose tolerance test
pres = Diastolic blood pressure (mm Hg)
skin = Triceps skin fold thickness (mm)
test = 2-Hour serum insulin (mu U/ml)
mass = Body mass index (weight in kg/(height in m)^2)

pedi = Diabetes pedigree function
age = Age (years)
class = Class variable (1:tested positive for diabetes, 0: tested negative for diabetes)

Your Task:
Question-1: Using attached data set of “pima-indian-diabetes”. Implementing Logistic Regression using given 8 features in the data.

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Expert Answer

Step 1/1
Here is an implement.

OR