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

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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.

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KSSV
KSSV 2019-4-9
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}) ;
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