Principal Component Analysis (PCA) in R

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Easy ML

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You know what starting with this video I was...why is he so loud?
But at the end you made my day dude...and I subscribed your channel .. thanks a lot... bring more videos ..keep the learning on😃

parametersofstatistics

Thank you Sir. This video is so much helpful and

moubonnydas

Thank You very-very much! It is certainly one of the best explanations. Very helpful! But I have got some questions. 1) I can not understand what do we do next with the PCAs? Shall I use it for multiple regression along with other variables or for clustering? 2) Can I reevaluate impact of variables using loading data? For instance, I use 5 variables to build PCAs. My PCA1 and 2 describe about 85% of variability, but each PCA does not connect to - lets say - the 3rd variable. May be I should delete the 3rd variable and run the analysis with only 4 others? Will this improve the outcome? 3) Why are some spaces blank in loadings (minute 6.28 on the video) - like Sepal.Width vs Comp.1? 4) And the final - body mass index is given as an example of PCA outcome. Does that mean that we can retrieve PCA1 and name it as a sort of new stable variable? Or BMI is just an example of data dimension reduction that does not correspond to PCA directly? Thats a lot of questions - but I really wonder...

alinaastakhova

Thanks very much . Well explained and very useful

robtaylor

Awesome video...kudos... u said the variables are eligible for PCA as they have mean(cor(mydata)) value as 0.46( u said it was high and good enough) - What is the value range for PCA?? :)

prithvivasireddy

us data analysts learning more than necessary about plant terminology..

ThinkLikeCheese

The mean of my cor(data) is 0.45. Is it not eligible for pca? What should i use for variable selection then?

Aloneincrowd

I have a error “x” must be numeric... any solution?

Hi i want to ask, if i use 2 comp from my PCA, how to know which variable is in Comp.1 and which is in Comp.2?? Do i only need to see in PCA$loadings which one has the larger value among all of them for each Comp?? thank you! ^^

leyyazea

While computing mean correlation you shouldve get rid of the diag and upper trig (?)

djangoworldwide

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