Classification of obesity levels based on eating habits and physical condition

This dataset encompasses information intended for the assessment of obesity levels among individuals in the nations of Mexico, Peru, and Colombia.
The main dataset is prepared by other authors in the article (https://doi.org/10.1016/j.dib.2019.104344) I have only used this dataset to perform my final project related to the Homework Assignment 6: Machine Learning Application in Project Dataset. Here is some detaied explanation about the dataset: 
The attributes related with eating habits are:

Frequent consumption of high caloric food (FAVC)
Frequency of consumption of vegetables (FCVC)
Number of main meals (NCP)
Consumption of food between meals (CAEC)
Consumption of water daily (CH20)
Consumption of alcohol (CALC)
The attributes related with the physical condition are:

Calories consumption monitoring (SCC)
Physical activity frequency (FAF)
Time using technology devices (TUE)
Transportation used (MTRANS)
other variables obtained were:

Gender
Age
Height
Weight
family history with overweight
SMOKE activity
Finally, all data was labeled and the class variable NObesity was created with the values of:
a) Insufficient Weight
b) Normal Weight
c) Overweight Level I
d) Overweight Level II
e) Obesity Type I
f) Obesity Type II
g) Obesity Type III