What's the meaning of dimensionality and what is it for this data?
May 5, 2015 · I've been told that dimensionality is usually referred to attributes or columns of the dataset. But in this case, does it include Class1 and Class2? and does dimensionality mean, the …
dimensionality reduction - Relationship between SVD and PCA. How to …
Jan 22, 2015 · However, it can also be performed via singular value decomposition (SVD) of the data matrix $\mathbf X$. How does it work? What is the connection between these two approaches? …
Can the elbow method be used in PCA (Principal ... - Cross Validated
May 16, 2025 · I’m wondering if a similar technique can be applied to PCA for dimensionality reduction. Specifically, can we use an "elbow" in the explained variance plot to determine the best number of …
What is the curse of dimensionality? - Cross Validated
I cannot expound, but I believe I've heard what sound like three different versions of the curse: 1) higher dimensions mean an exponentially-increasing amount of work, and 2) in higher dimensions you will …
machine learning - Why is dimensionality reduction used if it almost ...
Jan 9, 2022 · Why is dimensionality reduction used if it almost always reduces the explained variation? Ask Question Asked 4 years, 2 months ago Modified 4 years ago
Why is Euclidean distance not a good metric in high dimensions?
May 20, 2014 · I read that 'Euclidean distance is not a good distance in high dimensions'. I guess this statement has something to do with the curse of dimensionality, but what exactly? Besides, what is 'high
Why is t-SNE not used as a dimensionality reduction technique for ...
Apr 13, 2018 · And Dimensionality reduction is also projection to a (hopefuly) meaningful space. But dimensionality reduction has to do so in a uninformed way -- it does not know what task you are …
Curse of dimensionality- does cosine similarity work better and if so ...
Apr 19, 2018 · When working with high dimensional data, it is almost useless to compare data points using euclidean distance - this is the curse of dimensionality. However, I have read that using …
Difference between dimensionality reduction and clustering
Apr 29, 2018 · Most of the research papers and even the package creators for example hdbscan recommends dimensionality reduction before applying clustering esp. If the number of dimensions …
Why is dimensionality reduction always done before clustering?
I learned that it's common to do dimensionality reduction before clustering. But, is there any situation that it is better to do clustering first, and then do dimensionality reduction?