After applying PCA algorithm, how to display its principal component?thanks!! [image]

There have been quite a few discussions on this, use the search function on discourse to find e.g. [image] PCA Output? Statistics To support this request: …so better check that we don’t choose an approach/terminology which is only familiar to psychologists. The use of…

This was already answered by @nilshg in the post mentioned above. You need the projection matrix, which you can get with projection(M). You can read more about the properties in the docs . using MultivariateStats X = rand(4,5) M = fit(PCA, X; maxoutdim=2) proj = projection(M)[:, 1]

thanks，but it does not tell me which is the extracted principal component?it only several numbers.

Because I want to plot these principal components

@abcde , I understand you, and I got into this a while back. I was not completely satisfied and so I addressed R about Julia. Here is just a code snippet: using RCall ... R"library(psych)" # Estimate the number of HK's using the R function scree: HK_R = R"scree($PCA_Daten)" ... PCA_Modell = R"prin…

Fair enough. Each column of proj gives the corresponding PCA axis. I assumed you only wanted the first axis, since you didn’t provide the data you wanted to transform.

To visualize your data in 2D with PCA, you can transform your data X. using PyCall, MultivariateStats, Plots data = pyimport("sklearn.datasets") # Generate labeled data with 3 classes X, y = data.make_blobs(n_samples=1000, n_features = 10, centers = 3, cluster_std = 3, random_state=0) # Columns …

In BetaML you have what I believe is one of the simplest approach (disclaimer: I am the author): “”’ pca(X;K,error) Perform Principal Component Analysis returning the matrix reprojected among the dimensions of maximum variance. Parameters: X : The (N,D) data to reproject K : The number of d…

If the way the package works is bothering you, it’s only a few lines of code to get them yourself using LinearAlgebra. For example, in most cases I’m familiar with, users want the components ordered from largest eignvalue to smallest. Given data matrix in x with rows as observations and columns as v…

A question ahout PCA

Specific Domains Optimization (Mathematical)

nilshg June 26, 2020, 1:45pm 2

There have been quite a few discussions on this, use the search function on discourse to find e.g.

Topic		Replies	Views
PCA Output? Statistics	25	6767	February 17, 2022
plot PCA projection: How interpret New to Julia question , package , plotting , pyplot , packages	5	1856	March 26, 2018
A question about PCA and visualization Performance question	1	402	June 26, 2020
Pca question Optimization (Mathematical)	2	765	June 22, 2021
Problem realization of PCA Optimization (Mathematical) question	2	616	February 4, 2022

A question ahout PCA

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