Estimation of Obesity Levels Based On Eating Habits and Physical Condition
Donated on 8/26/2019
This dataset include data for the estimation of obesity levels in individuals from the countries of Mexico, Peru and Colombia, based on their eating habits and physical condition.
Dataset Characteristics
Multivariate
Subject Area
Health and Medicine
Associated Tasks
Classification, Regression, Clustering
Feature Type
Integer
# Instances
2111
# Features
16
Dataset Information
Additional Information
This dataset include data for the estimation of obesity levels in individuals from the countries of Mexico, Peru and Colombia, based on their eating habits and physical condition. The data contains 17 attributes and 2111 records, the records are labeled with the class variable NObesity (Obesity Level), that allows classification of the data using the values of Insufficient Weight, Normal Weight, Overweight Level I, Overweight Level II, Obesity Type I, Obesity Type II and Obesity Type III. 77% of the data was generated synthetically using the Weka tool and the SMOTE filter, 23% of the data was collected directly from users through a web platform.
Has Missing Values?
No
Introductory Paper
By Fabio Mendoza Palechor, Alexis De la Hoz Manotas. 2019
Published in Data in Brief
Variables Table
| Variable Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| Gender | Feature | Categorical | Gender | no | ||
| Age | Feature | Continuous | Age | no | ||
| Height | Feature | Continuous | no | |||
| Weight | Feature | Continuous | no | |||
| family_history_with_overweight | Feature | Binary | Has a family member suffered or suffers from overweight? | no | ||
| FAVC | Feature | Binary | Do you eat high caloric food frequently? | no | ||
| FCVC | Feature | Integer | Do you usually eat vegetables in your meals? | no | ||
| NCP | Feature | Continuous | How many main meals do you have daily? | no | ||
| CAEC | Feature | Categorical | Do you eat any food between meals? | no | ||
| SMOKE | Feature | Binary | Do you smoke? | no |
0 to 10 of 17
Additional Variable Information
Read the article (https://doi.org/10.1016/j.dib.2019.104344) to see the description of the attributes.
Class Labels
Insufficient Weight, Normal Weight, Overweight Level I, Overweight Level II, Obesity Type I, Obesity Type II, and Obesity Type III
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset estimation_of_obesity_levels_based_on_eating_habits_and_physical_condition = fetch_ucirepo(id=544) # data (as pandas dataframes) X = estimation_of_obesity_levels_based_on_eating_habits_and_physical_condition.data.features y = estimation_of_obesity_levels_based_on_eating_habits_and_physical_condition.data.targets # metadata print(estimation_of_obesity_levels_based_on_eating_habits_and_physical_condition.metadata) # variable information print(estimation_of_obesity_levels_based_on_eating_habits_and_physical_condition.variables)
Estimation of Obesity Levels Based On Eating Habits and Physical Condition . (2019). UCI Machine Learning Repository. https://doi.org/10.24432/C5H31Z.
@misc{misc_estimation_of_obesity_levels_based_on_eating_habits_and_physical_condition__544,
title = {{Estimation of Obesity Levels Based On Eating Habits and Physical Condition }},
year = {2019},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5H31Z}
}DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.