Top "Pca" questions

Principal component analysis (PCA) is a statistical technique for dimension reduction often used in clustering or factor analysis.

Matlab - PCA analysis and reconstruction of multi dimensional data

I have a large dataset of multidimensional data(132 dimensions). I am a beginner at performing data mining and I want …

matlab data-mining pca
Principal components analysis using pandas dataframe

How can I calculate Principal Components Analysis from data in a pandas dataframe?

python pandas pca scientific-computing principal-components
R function prcomp fails with NA's values even though NA's are allowed

I am using the function prcomp to calculate the first two principal components. However, my data has some NA values …

r pca na
Feature/Variable importance after a PCA analysis

I have performed a PCA analysis over my original dataset and from the compressed dataset transformed by the PCA I …

python machine-learning scikit-learn pca feature-selection
How to solve prcomp.default(): cannot rescale a constant/zero column to unit variance

I have a data set of 9 samples (rows) with 51608 variables (columns) and I keep getting the error whenever I try …

r matrix pca prcomp
Change point colors and color of frame/ellipse around points

I want to start by saying that I am a novice user of R and especially of this website, so …

r ggplot2 pca ggfortify
Factor Loadings using sklearn

I want the correlations between individual variables and principal components in python. I am using PCA in sklearn. I don't …

python scikit-learn pca
R - 'princomp' can only be used with more units than variables

I am using R software (R commander) to cluster my data. I have a smaller subset of my data containing 200 …

r cluster-analysis k-means pca r-commander
PCA first or normalization first?

When doing regression or classification, what is the correct (or better) way to preprocess the data? Normalize the data -&…

machine-learning normalization classification regression pca