R/diabetes_data.R

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

#' Diabetes datasets
#' @docType data
#' @keywords diabetes machine learning classification
#' @format A data frame with 520 rows and 17 variables:
#' \describe{
#'   \item{Age}{age of the patient presenting with diabetes}
#'   \item{Gender}{gender of the patient with diabetes}
#'   \item{ExcessUrination}{if the patient has a history of excessive urination}
#'   \item{Polydipsia}{abnormal thurst, accompanied by the excessive intake of water or fluid}
#'   \item{WeightLossSudden}{Sudden weight loss that has recently occured}
#'   \item{Fatigue}{Fatigue or weakness}
#'   \item{Polyphagia}{excessive or extreme hunger}
#'   \item{GenitalThrush}{patient has thrush fungus on or near their genital region}
#'   \item{BlurredVision}{history of blurred vision}
#'   \item{Itching}{skin itching}
#'   \item{Irritability}{general irritability and mood issues}
#'   \item{DelayHealing}{delayed healing of wounds}
#'   \item{PartialPsoriasis}{partial psoriasis on the body}
#'   \item{MuscleStiffness}{stiffness of the muscles}
#'   \item{Alopecia}{scalp alopecia and hair shedding}
#'   \item{Obesity}{Classified as obese}
#'   \item{DiabeticClass}{Class label to indicate whether the patient is diabetic or not}
#' }
#' @source Collected by Gary Hutson \email{hutsons-hacks@outlook.com}, 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)
"diabetes_data"