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: