# Estimating the # of Principal components based on variance explained

I am running PCA on a dataset with dimensions 1460(n) * 307(p). Upon running PCA, I obtain the below plot of variance explained and the number of components. I am trying to estimate the number of PCs to select for my training dataset.

Based on the plot below, It appears that around 75% of the variance is explained/captured by 50 PCs. So, selecting 50 PCs is a reasonable estimate.

How would you interpret the below plot and estimate # of PCs to select?

Thanks!

• support.minitab.com/en-us/minitab/17/topic-library/… – SmallChess Mar 22 '17 at 3:11
• You choose your desired percentage (80%, 90%). You use it to select your components. – SmallChess Mar 22 '17 at 3:12
• @Student T yeah - the scree plot shows a steep curve until like ~20 PCs and then it's horizontal line from then on. – kms Mar 22 '17 at 3:15
• Answers in this post go into detail on methods for appropriately selecting the number of components. The Valle paper referred to is a very good introduction to this topic: stats.stackexchange.com/questions/100143/… – Deathkill14 Mar 22 '17 at 6:42