How to use kmeans function on data stored by datastore function?

I'm trying to cluster big data using kmeans, i found a code that can do something similar here you are

    Mu = bsxfun(@times,ones(20,30),(1:20)'); % Gaussian mixture mean
    rn30 = randn(30,30);
    Sigma = rn30'*rn30; % Symmetric and positive-definite covariance
    Mdl = gmdistribution(Mu,Sigma);

    rng(1); % For reproducibility
    X = random(Mdl,10000);
   pool = parpool;                      % Invokes workers
   stream = RandStream('mlfg6331_64');  % Random number stream
   options = statset('UseParallel',1,'UseSubstreams',1,...
    'Streams',stream);
   tic; % Start stopwatch timer
   [idx,C,sumd,D] = kmeans(X,20,'Options',options,'MaxIter',10000,...
    'Display','final','Replicates',10);
   toc % Terminate stopwatch timer

But as you can see, X is double.

My problem is that i have a file named HIS.csv and i used the datastore function to store it as follows

    ds = datastore('HIS_all.csv', 'DatastoreType', 'tabulartext','TreatAsMissing', 'NA');
when i tried 

     [idx,C,sumd,D] = kmeans(ds,20,'Options',options,'MaxIter',10000, 'Display','final','Replicates',10);
i get the following error

     Undefined function 'isnan' for input arguments of type 'matlab.io.datastore.TabularTextDatastore'.

     Error in kmeans (line 158)
     wasnan = any(isnan(X),2);
Any suggestions?

Answer 1

[Josh Meyer]

Datastore is just a framework for loading small chunks of the data at a time, so you can't call generic functions directly on the datastore. Instead try converting the datastore into a tall array first:

   T = tall(ds);

The kmeans function supports tall arrays, so once the data is in this format you can use the function. Note that there are some limitations to using kmeans on a tall array, so some of the NV pairs you specified might not work. The limitations are outlined here:

Tall Array Support, Usage Notes, and Limitations