Question

1) What are the differences and similarities between factor analysis and PCA. Focus on the equations that are produced

2) What are some of the challenges with KNN. How would you advise someone who decides to use KNN?

Answer 1

Note: If more than one question was asked, we were instructed to answer only one. Therefore, answering the first question.

Differences between factor analysis and PCA.

* PCA involves extracting linear components of the observed variables, whereas, factor analysis works on the predicting variable

*In PCA, the components are orthogonal linear components that maximize the variance. in FA, it is the linear combinations that maximize the portion of the variance, that is shared.

Similarities between factor analysis and PCA

* Both can be seen as data reduction or complexity reduction techniques, both try to capture larger variances within given data

* If you run both of the tests in a software, the output of the both looks the same