Homework 8
(10 point)
– Download at least 200 Pubmed articles (abstract, title or whatever you prefer). 100 should include the term ¡°obesity¡± and the other 100 should include the term ¡°cancer¡±. If your system is running too slow for the next step you can download 50 from each category.
– Analyze their textual corpus in a way that we can feed them into a dimensionality reduction method.
– Apply following dimensionality reductions on the text: PCA (3 points), tSNE (3 points), UMAP (4 points).
-You need to prepare a report on your tasks and findings along with a video file describing what you have done. You can copy paste your codes, its results and your description into a Word document, Python Notebook or you can use R notebook.
-Your deadline for delivering this home work is written on the blackboard online. Please feel free to ask your question and prepare it for presentation for the next session.
Hint: You might use this resource for python: https://www.scikit- yb.org/en/latest/api/text/index.html, and R: https://cran.r- project.org/web/packages/umap/vignettes/umap.html , https://www.r-bloggers.com/quick-and- easy-t-sne-analysis-in-r/
But, there is no guarantee that if those links and hints are helpful.