Re: [R] Regarding Principal Component Analysis result Interpretation

This list is about R programming, not statistics, although they do often intersect. Nevertheless, this discussion seems to be all about the latter, not the former, so I think you would do better bringing it to a statistics list like stats.stackexchange.com rather than here. Cheers, Bert Bert

Re: [R] Regarding Principal Component Analysis result Interpretation

First, see the example at https://isezen.github.io/PCA/ > On 15 Sep 2017, at 13:43, Shylashree U.R wrote: > > Dear Sir/Madam, > > I am trying to do PCA analysis with "iris" dataset and trying to interpret > the result. Dataset contains 150 obs of 5 variables > >

Re: [R] Regarding Principal Component Analysis result Interpretation

Usually, PCA is used for a large number of features. FactoMineR [1] package provides a couple of examples, check for temperature example. But you may want to consult to basic PCA material as well, I suggest a book from Chris Bishop [2]. [1]

[R] Regarding Principal Component Analysis result Interpretation

Dear Sir/Madam, I am trying to do PCA analysis with "iris" dataset and trying to interpret the result. Dataset contains 150 obs of 5 variables Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.13.5 1.4 0.2