Question

Which of the following statements is true of principal component analysis (PCA) and cluster analysis?



(a) PCA and cluster analysis are incompatible techniques, only one of them can be applied to the same data


(b) PCA is a data reduction technique and cluster analysis is a dimensionality reduction technique


(c) Cluster analysis is a data reduction technique and PCA is a dimensionality reduction technique


(d) The main goal of cluster analysis is to identify redundant variables and the main goal of PCA is to create homogeneous groups of observations

Answer 1

Answer:

• Principal Component Analysis (PCA) We will be focusing on the visualization part. In this regard, PCA can be thought of as a clustering algorithm not unlike other clustering methods, such as k-means clustering
• Cluster analysis is a method of unsupervised learning where the goal is to discover groups in the data; the groups are not known in advance (although you may know the number of groups). ... PCA is a method of data reduction.