Does it make sense to combine PCA and LDA? - Cross Validated
2016年6月3日 · PCA and LDA, as dimensionality reduction techniques, are very different. Sometimes people do PCA prior LDA, but it has its risks to throw away (with the discarded …
When would you use PCA rather than LDA in classification?
LDA is used to carve up multidimensional space. PCA is used to collapse multidimensional space. PCA allows the collapsing of hundreds of spatial dimensions into a handful of lower spatial …
What is the difference between PCA and LDA? - Cross Validated
2020年5月19日 · Principal Component Analysis (PCA), Factor Analysis (FA), and Linear Discriminant Analysis (LDA) are all used for feature reduction. They all depend on using …
classification - Does PCA followed by LDA make sense, when there …
2015年1月25日 · Without reading the whole question but in reply to the last ask The key question is: does PCA followed by LDA make sense? I'd reply "Often, not". In a sense, the two …
LDA, PCA and k-means: how are they related? - Cross Validated
2015年2月6日 · I am trying to understand how linear discriminant analysis (LDA) is related to principal component analysis (PCA) and k-means clustering method. As an example, here is a …
How to correctly apply LDA following PCA? - Cross Validated
If your wish is the first one I said about, i.e. only the fact that n<p bothers you and only this fact forces you to apply PCA, - then you should retain 28 (all but one last) components in PCA and …
PCA, LDA, CCA, and PLS - Cross Validated
2015年1月30日 · How are PCA, LDA, CCA, and PLS related? They all seem "spectral" and linear algebraic and very well understood (say 50+ years of theory built around them). They are used …
Proportion of explained variance in PCA and LDA
I have some basic questions regarding PCA (principal component analysis) and LDA (linear discriminant analysis): In PCA there is a way to calculate the proportion of variance explained. …
pca - LDA - solving singularity problem of within classes matrix ...
2019年1月7日 · LDA tries to maximise the ratio of between-class-scatter to within-class-scatter. That is - it seeks to find a projection where there is a big gap between the classes and small …
Using PCA, clustering, and LDA together - Cross Validated
2015年11月11日 · LDA and PCA are indeed often used together, but without the k-means performed in the middle. One use of PCA + LDA approach is for applying LDA in situations …