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Table 2 Detailed overview of PIMA dataset features

From: An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques

S. No

Selected feature

Details

Range

Average

1

Pregnancies

(F1)

The frequency with which

a woman gives birth

0-17

3.85

2

Glucose

(F2)

Plasma glucose levels at 2 hours in

a glucose tolerance test administered orally

0-199

120.90

3

Blood Pressure

(F3)

Diastolic blood pressure (when blood flows

into the arteries that connect the heart)

(mm Hg)

0-122

69.11

4

Skin Thickness

(F4)

The thickness of the triceps skin fold (mm)

0-99

20.54

5

Insulin

(F5)

Insulin concentration in serum throughout

a 2-hour time period (mu U/ml)

0-846

79.81

6

BMI

(F6)

Body mass index

(weight in kg/(height in m2)

0-67.1

31.99

7

Diabetes Pedigree

Function

(F7)

The function that calculates diabetes

risk based on family history

0.08-2.42

0.47

8

Age

(F8)

The participants age in years

21-81

33.24

9

Outcome

(Label)

Diabetes class variable Yes means that

the patient has diabetes, and

No means that the patient

doesn’t have diabetes.

Yes/No

Yes/No