This dataset is used to estimate obesity levels based on eating habits and physical condition. The data originates from the UCI Machine Learning Repository and has been preprocessed to include both predictors and a target variable.
The dataset is provided as a list with two components:
A data frame containing various predictors related to lifestyle, eating habits, and physical condition. The variables include:
The age of the individual in years.
The height of the individual in meters.
Binary variable indicating whether the individual has a family history of overweight (1 = yes, 0 = no).
Binary variable indicating whether the individual frequently consumes high-calorie foods (1 = yes, 0 = no).
The frequency of consumption of vegetables in meals.
The number of main meals consumed per day.
Categorical variable indicating the frequency of consumption of food between meals.
Typical levels include "no", "sometimes", "frequently", and "always".
Binary variable indicating whether the individual smokes (1 = yes, 0 = no).
Daily water consumption (typically in liters).
Binary variable indicating whether the individual monitors calorie consumption (1 = yes, 0 = no).
The frequency of physical activity.
The time spent using electronic devices (e.g., screen time in hours).
Categorical variable indicating the frequency of alcohol consumption.
Typical levels include "no", "sometimes", "frequently", and "always".
Binary variable indicating the gender of the individual (1 = male, 0 = female).
A list containing two elements:
A numeric vector representing the weight of the individual (used as the regression target).
A factor indicating the obesity level classification. The levels are derived from the original nobeyesdad variable in the dataset.
data(obesity)A list with two components:
A data frame containing various predictors related to eating habits, physical condition, and lifestyle.
A list with two elements: regression (weight in kilograms) and class (obesity level classification).
Palechor, Fabio Mendoza, and Alexis De la Hoz Manotas. "Dataset for estimation of obesity levels based on eating habits and physical condition in individuals from Colombia, Peru and Mexico." Data in brief 25 (2019): 104344.