To deal with the data, we have to load it to matlab and express it with variables.
%load data to matlab rawdata = load('E:\Pattern Recognition\Data Mining Repository\adult\resource\converted_data.data'); %get data of all fields age = rawdata(:,1)'; workclass = rawdata(:,2)'; fnlwgt = rawdata(:,3)'; education = rawdata(:,4)'; education_num = rawdata(:,5)'; marital_status = rawdata(:,6)'; occupation = rawdata(:,7)'; relationship = rawdata(:,8)'; race = rawdata(:,9)'; sex = rawdata(:,10)'; capital_gain = rawdata(:,11)'; capital_loss = rawdata(:,12)'; hours_per_week = rawdata(:,13)'; native_country = rawdata(:,14)'; isover5 = rawdata(:,15)'; [i,j] = size(rawdata); image(1) range = (1:1:100); [n,m] = hist(age,range); plot(range, n); hold on plot(range, n);
In this way, we get the distribution of all ages in the survey: