Skip to main content
Data Science

Return to Question

deleted 60 characters in body; edited title
Source Link
GabS
GabS
  • 111
  • 4

How does K-Means clustering help in the analysis of Word2vec embeddings

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA & TSNE to visualise the data. I have got 6 clusters which are well separated. Now I want to know, what this six clusters represent. In other words, I would likecreate a "Word-Cloud" with respect to seeeach of the which "words" belongs to cluster 0 and so onlabels. Can one one give an idea how to do that. Thank you.

How does K-Means clustering help in the analysis of Word2vec embeddings

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA & TSNE to visualise the data. I have got 6 clusters which are well separated. Now I want to know, what this six clusters represent. In other words, I would like to see the which "words" belongs to cluster 0 and so on. Can one one give an idea how to do that. Thank you.

K-Means clustering in the analysis of Word2vec embeddings

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA & TSNE to visualise the data. I have got 6 clusters which are well separated. Now I want to create a "Word-Cloud" with respect to each of the cluster labels. Can one one give an idea how to do that. Thank you.

added 14 characters in body
Source Link
GabS
GabS
  • 111
  • 4

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA & TSNE to visualise the data. I have got 6 clusters which are well separated. Now I want to know, what this six clusters represent. In other words, I would like to know what does 0, 1, 2, 3, 4, 5see the which "words" belongs to cluster stand0 and so on. Can one one give an idea how to do that. Thank you.

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA to visualise the data. I have got 6 clusters which are well separated. Now I want to know, what this six clusters represent. In other words, I would like to know what does 0, 1, 2, 3, 4, 5 cluster stand. Can one one give an idea how to do that. Thank you.

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA & TSNE to visualise the data. I have got 6 clusters which are well separated. Now I want to know, what this six clusters represent. In other words, I would like to see the which "words" belongs to cluster 0 and so on. Can one one give an idea how to do that. Thank you.

Source Link
GabS
GabS
  • 111
  • 4

How does K-Means clustering help in the analysis of Word2vec embeddings

I have a yelp-review dataset. I have done a word2vector embedding on the text column of the yelp-review. I am using unsupervised leaning K-means and PCA to visualise the data. I have got 6 clusters which are well separated. Now I want to know, what this six clusters represent. In other words, I would like to know what does 0, 1, 2, 3, 4, 5 cluster stand. Can one one give an idea how to do that. Thank you.