How to smart procrustes align in gensim?









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I am using the following code provided by gensim.



Link to the code: https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf



I have 5 word2vec models (i.e. for 2011, 2012, 2013, 2014, 2015) trained and I would like to combine them using this code.



Do we have to combine them in the chronological order? (python method in code: def smart_procrustes_align_gensim(base_embed, other_embed, words=None)



In other words;



1. Combine 2011 and 2012 -> get combined model 2011_20122. 
2. Combine 2011_2012 and 2013 -> get combined model 2011_2012_2013

3. Combine 2011_2012_2013 and 2014 -> get combined model 2011_2012_2013_2014

4. Combine 2011_2012_2013_2014 and 2015 -> get combined model 2011_2012_2013_2014_2015


Please kindly let me know your thoughts on this.










share|improve this question



























    up vote
    0
    down vote

    favorite












    I am using the following code provided by gensim.



    Link to the code: https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf



    I have 5 word2vec models (i.e. for 2011, 2012, 2013, 2014, 2015) trained and I would like to combine them using this code.



    Do we have to combine them in the chronological order? (python method in code: def smart_procrustes_align_gensim(base_embed, other_embed, words=None)



    In other words;



    1. Combine 2011 and 2012 -> get combined model 2011_20122. 
    2. Combine 2011_2012 and 2013 -> get combined model 2011_2012_2013

    3. Combine 2011_2012_2013 and 2014 -> get combined model 2011_2012_2013_2014

    4. Combine 2011_2012_2013_2014 and 2015 -> get combined model 2011_2012_2013_2014_2015


    Please kindly let me know your thoughts on this.










    share|improve this question

























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      I am using the following code provided by gensim.



      Link to the code: https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf



      I have 5 word2vec models (i.e. for 2011, 2012, 2013, 2014, 2015) trained and I would like to combine them using this code.



      Do we have to combine them in the chronological order? (python method in code: def smart_procrustes_align_gensim(base_embed, other_embed, words=None)



      In other words;



      1. Combine 2011 and 2012 -> get combined model 2011_20122. 
      2. Combine 2011_2012 and 2013 -> get combined model 2011_2012_2013

      3. Combine 2011_2012_2013 and 2014 -> get combined model 2011_2012_2013_2014

      4. Combine 2011_2012_2013_2014 and 2015 -> get combined model 2011_2012_2013_2014_2015


      Please kindly let me know your thoughts on this.










      share|improve this question















      I am using the following code provided by gensim.



      Link to the code: https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf



      I have 5 word2vec models (i.e. for 2011, 2012, 2013, 2014, 2015) trained and I would like to combine them using this code.



      Do we have to combine them in the chronological order? (python method in code: def smart_procrustes_align_gensim(base_embed, other_embed, words=None)



      In other words;



      1. Combine 2011 and 2012 -> get combined model 2011_20122. 
      2. Combine 2011_2012 and 2013 -> get combined model 2011_2012_2013

      3. Combine 2011_2012_2013 and 2014 -> get combined model 2011_2012_2013_2014

      4. Combine 2011_2012_2013_2014 and 2015 -> get combined model 2011_2012_2013_2014_2015


      Please kindly let me know your thoughts on this.







      python gensim






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 12 at 3:28

























      asked Nov 12 at 3:16









      J Cena

      343116




      343116



























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