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Hard time finding literature on feature clustering using Principal Component Analysis

Looks like you want go for unsupervised methods for feature selection. You can use PCA but it might not be that effective. I would suggest to go through these links. https://machinelearningmastery....
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Hard time finding literature on feature clustering using Principal Component Analysis

I am not sure PCA is quite what you are after. I think it may help to visualize what you are after. I think the image is as follows for 5 features with 2 records (i.e. 2 rows 5 columns): Here, ...
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Does PCA helps to include all the variables even if there is high collinearity among variables?

When using PCA, you should not try to interpret the single features anymore. The principal components are multiple linear combinations of your variables that should not be related to the original ...
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Dimensionality Reduction of Curved Structural Data

This is a tentative answer. In general PCA may yield good results even if the space is not strictly flat. However there are variations of PCA, like PGA (ie Principal Geodesic Analysis) which takes ...
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