Linked Questions

156
votes
7answers
118k views

PCA on correlation or covariance?

What are the main differences between performing principal component analysis (PCA) on the correlation matrix and on the covariance matrix? Do they give the same results?
17
votes
3answers
17k views

Why do we divide by the standard deviation and not some other standardizing factor before doing PCA?

I was reading the following justification (from cs229 course notes) on why we divide the raw data by its standard deviate: even though I understand what the explanation is saying, it is not clear to ...
7
votes
1answer
8k views

Normalizing all the variarbles vs. using scale=TRUE option in prcomp in R

What is the difference between normalizing the variables and doing PCA; using scale=TRUE option (without normalizing the variables) in ...
5
votes
1answer
12k views

How to normalize time series?

This is a general question on normalization of data so that all the variables are within the same range. Why do we normalize data in pattern classification? How to normalize time series which is ...
2
votes
1answer
2k views

Do you standardize the data before PCA whitening?

I have a data set ranged in different scales as well as some variables are sparse, for example, ...
1
vote
1answer
2k views

Should I standardize or normalize variables before conducting a principal components analysis

I am very confused as I am reading through PCA. Some sources say that I should normalize my data before applying PCA, and some sources say that I should standardize my data before applying PCA. I know ...
1
vote
2answers
334 views

Does standardization compromises Principal Component Analysis? [duplicate]

I've been dealing with PCA over the past week and I ended up with a requirement for performing PCA (in Python Machine Learning Book by Sebastian Raschka): Note that the PCA directions are highly ...
1
vote
1answer
733 views

data normalization after dimension reduction for classification

The classifier is KNN or RBF-SVM. After doing dimension reduction (e.g., PCA, LDA or KPCA, KLDA), does it need to do normalization before classification? In LIBSVM ...
0
votes
0answers
94 views

Why is scaling the data needed before principal component analysis (PCA) [duplicate]

I recognize that there are many questions on Cross Validated about scaling and PCA, but, after reading all of them, I still can't find the answer to my question. Several people have said that the ...
1
vote
0answers
44 views

Scaling Variables in PCA, yet all on the same scale

I know this topic of scaling and normalizing variables for PCA has been posted on a lot, 1, 2, 3. However, I am performing PCA on coordinate data that is measured all on the same scale, i.e. (x,y) ...