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Ratings matrix plot


Is there an efficient way to implement a random crossover of individuals stored in a matrix?Deep NN architecture for predicting a matrix from two matricesMatrix Dimension for Linear regression coefficientsMachine learning to predict 8*8 matrix values using three independent matricesHow can the convolution operation be implemented as a matrix-vector multiplication?Which matrix represents the similarity between words when using SVD?






.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;








1












$begingroup$


Hello fellows and folks.



I have been looking to do this for 1 month and still cannot find the way to do it.



Here’s what’s going on:



I have a csv file called ratings.csv with the following structure:



userID, movieID, rating
3, 12, 5
2, 7, 6


The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:



pictiure



As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.



I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.



This is what I have tried so far:



tbl = readtable('ratings.csv');
users = categorical(tbl.userId);
movies = categorical(tbl.movieId);
xlabels = categories(users);
ylabels = categories(movies);

numusers = numel(xlabels);
nummovies = numel(ylabels);

x = double(users);
y = double(movies);
ratings = tbl.rating;
cdata = accumarray([y,x],ratings,[numusers,nummovies]);
h = heatmap(xlabels,ylabels,cdata);


But it throws me this error:




Error using accumarray



First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).











share|improve this question











$endgroup$


















    1












    $begingroup$


    Hello fellows and folks.



    I have been looking to do this for 1 month and still cannot find the way to do it.



    Here’s what’s going on:



    I have a csv file called ratings.csv with the following structure:



    userID, movieID, rating
    3, 12, 5
    2, 7, 6


    The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:



    pictiure



    As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.



    I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.



    This is what I have tried so far:



    tbl = readtable('ratings.csv');
    users = categorical(tbl.userId);
    movies = categorical(tbl.movieId);
    xlabels = categories(users);
    ylabels = categories(movies);

    numusers = numel(xlabels);
    nummovies = numel(ylabels);

    x = double(users);
    y = double(movies);
    ratings = tbl.rating;
    cdata = accumarray([y,x],ratings,[numusers,nummovies]);
    h = heatmap(xlabels,ylabels,cdata);


    But it throws me this error:




    Error using accumarray



    First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).











    share|improve this question











    $endgroup$














      1












      1








      1





      $begingroup$


      Hello fellows and folks.



      I have been looking to do this for 1 month and still cannot find the way to do it.



      Here’s what’s going on:



      I have a csv file called ratings.csv with the following structure:



      userID, movieID, rating
      3, 12, 5
      2, 7, 6


      The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:



      pictiure



      As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.



      I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.



      This is what I have tried so far:



      tbl = readtable('ratings.csv');
      users = categorical(tbl.userId);
      movies = categorical(tbl.movieId);
      xlabels = categories(users);
      ylabels = categories(movies);

      numusers = numel(xlabels);
      nummovies = numel(ylabels);

      x = double(users);
      y = double(movies);
      ratings = tbl.rating;
      cdata = accumarray([y,x],ratings,[numusers,nummovies]);
      h = heatmap(xlabels,ylabels,cdata);


      But it throws me this error:




      Error using accumarray



      First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).











      share|improve this question











      $endgroup$




      Hello fellows and folks.



      I have been looking to do this for 1 month and still cannot find the way to do it.



      Here’s what’s going on:



      I have a csv file called ratings.csv with the following structure:



      userID, movieID, rating
      3, 12, 5
      2, 7, 6


      The rating scale goes from 0 to 5 stars. I want to be able to plot the sparsity of the matrix like it’s done in the following picture:



      pictiure



      As you can see, ratings scale goes from 0 to 5 on the right. It is a very well thought plot.



      I have Matlab, Python, R etc. Could you come up with something and help me? I’ve tried hard but I cannot find the way to do it.



      This is what I have tried so far:



      tbl = readtable('ratings.csv');
      users = categorical(tbl.userId);
      movies = categorical(tbl.movieId);
      xlabels = categories(users);
      ylabels = categories(movies);

      numusers = numel(xlabels);
      nummovies = numel(ylabels);

      x = double(users);
      y = double(movies);
      ratings = tbl.rating;
      cdata = accumarray([y,x],ratings,[numusers,nummovies]);
      h = heatmap(xlabels,ylabels,cdata);


      But it throws me this error:




      Error using accumarray



      First input SUBS and third input SZ must satisfy ALL(MAX(SUBS)<=SZ).








      machine-learning recommender-system data-visualization






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited 1 hour ago









      malioboro

      796119




      796119










      asked 8 hours ago









      naveganteXnaveganteX

      1306




      1306




















          2 Answers
          2






          active

          oldest

          votes


















          2












          $begingroup$

          You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.






          share|improve this answer









          $endgroup$




















            1












            $begingroup$

            I did it!



            A = importdata('u.data');
            user_id = A(:, 1);
            movie_id = A(:, 2);
            rating = A(:, 3);

            % Build matrix R and w (weights matrix)
            R = zeros(943, 1682);
            w = zeros(943, 1682);
            for i=1:100000
            R(user_id(i), movie_id(i)) = rating(i);
            w(user_id(i), movie_id(i)) = 1;
            end


            m = HeatMap(R)
            ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
            colorbar('Peer', ax); % Turn the colorbar on
            caxis(ax, [0 5]); % Adjust the color limits


            Output:



            enter image description here






            share|improve this answer









            $endgroup$













              Your Answer








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              2 Answers
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              2 Answers
              2






              active

              oldest

              votes









              active

              oldest

              votes






              active

              oldest

              votes









              2












              $begingroup$

              You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.






              share|improve this answer









              $endgroup$

















                2












                $begingroup$

                You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.






                share|improve this answer









                $endgroup$















                  2












                  2








                  2





                  $begingroup$

                  You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.






                  share|improve this answer









                  $endgroup$



                  You're looking for a heatmap. Check out e.g. https://stackoverflow.com/q/33282368/3924118 (if you like Python more than the others). See also this documentation.







                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered 7 hours ago









                  nbronbro

                  3,3302826




                  3,3302826























                      1












                      $begingroup$

                      I did it!



                      A = importdata('u.data');
                      user_id = A(:, 1);
                      movie_id = A(:, 2);
                      rating = A(:, 3);

                      % Build matrix R and w (weights matrix)
                      R = zeros(943, 1682);
                      w = zeros(943, 1682);
                      for i=1:100000
                      R(user_id(i), movie_id(i)) = rating(i);
                      w(user_id(i), movie_id(i)) = 1;
                      end


                      m = HeatMap(R)
                      ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
                      colorbar('Peer', ax); % Turn the colorbar on
                      caxis(ax, [0 5]); % Adjust the color limits


                      Output:



                      enter image description here






                      share|improve this answer









                      $endgroup$

















                        1












                        $begingroup$

                        I did it!



                        A = importdata('u.data');
                        user_id = A(:, 1);
                        movie_id = A(:, 2);
                        rating = A(:, 3);

                        % Build matrix R and w (weights matrix)
                        R = zeros(943, 1682);
                        w = zeros(943, 1682);
                        for i=1:100000
                        R(user_id(i), movie_id(i)) = rating(i);
                        w(user_id(i), movie_id(i)) = 1;
                        end


                        m = HeatMap(R)
                        ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
                        colorbar('Peer', ax); % Turn the colorbar on
                        caxis(ax, [0 5]); % Adjust the color limits


                        Output:



                        enter image description here






                        share|improve this answer









                        $endgroup$















                          1












                          1








                          1





                          $begingroup$

                          I did it!



                          A = importdata('u.data');
                          user_id = A(:, 1);
                          movie_id = A(:, 2);
                          rating = A(:, 3);

                          % Build matrix R and w (weights matrix)
                          R = zeros(943, 1682);
                          w = zeros(943, 1682);
                          for i=1:100000
                          R(user_id(i), movie_id(i)) = rating(i);
                          w(user_id(i), movie_id(i)) = 1;
                          end


                          m = HeatMap(R)
                          ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
                          colorbar('Peer', ax); % Turn the colorbar on
                          caxis(ax, [0 5]); % Adjust the color limits


                          Output:



                          enter image description here






                          share|improve this answer









                          $endgroup$



                          I did it!



                          A = importdata('u.data');
                          user_id = A(:, 1);
                          movie_id = A(:, 2);
                          rating = A(:, 3);

                          % Build matrix R and w (weights matrix)
                          R = zeros(943, 1682);
                          w = zeros(943, 1682);
                          for i=1:100000
                          R(user_id(i), movie_id(i)) = rating(i);
                          w(user_id(i), movie_id(i)) = 1;
                          end


                          m = HeatMap(R)
                          ax = hm.plot; % 'ax' will be a handle to a standard MATLAB axes.
                          colorbar('Peer', ax); % Turn the colorbar on
                          caxis(ax, [0 5]); % Adjust the color limits


                          Output:



                          enter image description here







                          share|improve this answer












                          share|improve this answer



                          share|improve this answer










                          answered 2 hours ago









                          naveganteXnaveganteX

                          1306




                          1306



























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