Message-ID: <CAPtbhHwZSnSM2JTmHyspeSt6+GS8_SL_3cLs4MYhXyenhYCQ5w@mail.gmail.com>
Date: 2017-09-15T11:59:52Z
From: Suzen, Mehmet
Subject: Regarding Principal Component Analysis result Interpretation
In-Reply-To: <CAPvnpU9_rBuMKNH+JgbC5P8YM4OkJNUfe-MU0EzFCKAZcOqSXg@mail.gmail.com>
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] https://cran.r-project.org/web/packages/FactoMineR/vignettes/clustering.pdf
[2] http://www.springer.com/de/book/9780387310732?referer=www.springer.de