diabetes_data: Diabetes datasets

In MLDataR: Collection of Machine Learning Datasets for Supervised Machine Learning

Diabetes datasets

Description

Diabetes datasets

Usage

diabetes_data

Format

A data frame with 520 rows and 17 variables:

Age

age of the patient presenting with diabetes

Gender

gender of the patient with diabetes

ExcessUrination

if the patient has a history of excessive urination

Polydipsia

abnormal thurst, accompanied by the excessive intake of water or fluid

WeightLossSudden

Sudden weight loss that has recently occured

Fatigue

Fatigue or weakness

Polyphagia

excessive or extreme hunger

GenitalThrush

patient has thrush fungus on or near their genital region

BlurredVision

history of blurred vision

Itching

skin itching

Irritability

general irritability and mood issues

DelayHealing

delayed healing of wounds

PartialPsoriasis

partial psoriasis on the body

MuscleStiffness

stiffness of the muscles

Alopecia

scalp alopecia and hair shedding

Obesity

Classified as obese

DiabeticClass

Class label to indicate whether the patient is diabetic or not

Source

Collected by Gary Hutson [e-mail], Dec-2021

Examples

library(dplyr)
data(diabetes_data)
# Convert diabetes data to factor'
diabetes_data <- diabetes_data %>%
 glimpse() %>%
 mutate(DiabeticClass = as.factor(DiabeticClass))
 is.factor(diabetes_data$DiabeticClass)

MLDataR documentation built on Oct. 3, 2022, 5:08 p.m.