How to group a data set based on the ranges using machine learning techniques?

I have one year data of my daily consumption of food.

The sample dataset is given as in the data.xlsx

I want to classify the daily calory into following catogories usning machine learning techning(clustering). Can anybody help me?

Below 10 : Low

10-30 : medium

30- 50 : good diet

50-60 : heavy

more then 60 : bad diet.

Answer 1

[KSSV]

Using knnsearch

[num,txt,raw] = xlsread('data.xlsx') ; 
N = length(num) ; 
C = cell(N,1) ; 
C(num<10) = {'Low'} ; 
C(num>=10 & num<30) = {'Medium'} ; 
C(num>=30 & num<50) = {'Good'} ; 
C(num>=50 & num<60) = {'Heavy'} ; 
C(num>=60) = {'Bad'} ; 
T = table(C,num) 
s = input('Enter the Calory value:') ; 
idx = knnsearch(num,s) ;
fprintf('The enterd %d calory is %s\n',s,C{idx}) ; 

[Geethu T H]

Thank you so much for the quick reply. Can you please explain the working of machine learning techinque you have used in your code. Also is it possible to visualise the catogories?

[KSSV]

Can you please explain the working of machine learning techinque

YOu have lot of methods in ML.....I have just demonstrated quickly a single one using knnsearch. YOu can read it on your own.

[Geethu T H]

thank you

[KSSV]

Visualize:

idx = 1:N ; 
gscatter(idx,num,C)