In this pull request, I solve issues #19, #18, #17, and part of #3. In summary, this PR adds modifications that:
Solve the issues with the figures that were not loading;
Improve the explanation of clustering algorithms;
Improve the explanation of distance metrics, and add Mahalanobis distance to the content;
Improve the explanation of principal component analysis in the book;
Correct orthography across the material;
Matches versions across both languages.
The hierarchical clustering portion still needs considerable improvement in the presentation. This should not be complicated to repair given that the book now offers a detailed explanation of these algorithms.
The PCoA, CA, and NMDS need a very good makeover in both the presentation and the book. However, following up on previous discussions, I think it would be good to consider splitting this workshop in two. The introduction, dissimilarity measures, transformations and the PCA parts are really good and provide a detailed overview of these methods while explaining how to use R at the same time. With the improvement required for the clustering part, it will leave almost no space for the CA, PCoA, and NMDS parts to have a similar level of detail.
Please do not hesitate to reach out to me if you have any comments about this PR.
Hi all,
In this pull request, I solve issues #19, #18, #17, and part of #3. In summary, this PR adds modifications that:
The hierarchical clustering portion still needs considerable improvement in the presentation. This should not be complicated to repair given that the book now offers a detailed explanation of these algorithms.
The PCoA, CA, and NMDS need a very good makeover in both the presentation and the book. However, following up on previous discussions, I think it would be good to consider splitting this workshop in two. The introduction, dissimilarity measures, transformations and the PCA parts are really good and provide a detailed overview of these methods while explaining how to use R at the same time. With the improvement required for the clustering part, it will leave almost no space for the CA, PCoA, and NMDS parts to have a similar level of detail.
Please do not hesitate to reach out to me if you have any comments about this PR.
Talk to you soon!