I wanted to check over my answers based on these practice questions. Thanks
(1) True/False: Clustering is an unsupervised learning problem.
(2) True/False: Principal Components Analysis can be used to create a low dimensional projection of the data for use with clustering.
3) True/False: Common factors estimated using maximum likelihood estimation with a PROMAX rotation are orthogonal.
4) True/False: Common factors estimated using Iterated Principal Factor Analysis with a VARIMAX rotation are orthogonal.
5) True/False: In cluster analysis the choice of similarity measure will affect the cluster assignments.
6) True/False: When computing principal components the data should be standardized, i.e. the data should be centered and scaled to a (0,1) distribution.
7) True/False: Cluster analysis can only be performed on continuous variables.
8) True/False: Hierarchical clustering requires that the number of clusters be specified in advance.
9) True/False: Factor Analysis and Principal Components Analysis have the same objective of modeling the correlation structure in multivariate data.
10) True/False: Since cluster analysis is an unsupervised learning method, two different cluster partitions cannot be compared.
My answers:
1) True
2) false
3) true
4) false
5) true
6) true
7) false
8) false
9) false
10) true
(1) True/False: Clustering is an unsupervised learning problem.
(2) True/False: Principal Components Analysis can be used to create a low dimensional projection of the data for use with clustering.
3) True/False: Common factors estimated using maximum likelihood estimation with a PROMAX rotation are orthogonal.
4) True/False: Common factors estimated using Iterated Principal Factor Analysis with a VARIMAX rotation are orthogonal.
5) True/False: In cluster analysis the choice of similarity measure will affect the cluster assignments.
6) True/False: When computing principal components the data should be standardized, i.e. the data should be centered and scaled to a (0,1) distribution.
7) True/False: Cluster analysis can only be performed on continuous variables.
8) True/False: Hierarchical clustering requires that the number of clusters be specified in advance.
9) True/False: Factor Analysis and Principal Components Analysis have the same objective of modeling the correlation structure in multivariate data.
10) True/False: Since cluster analysis is an unsupervised learning method, two different cluster partitions cannot be compared.
My answers:
1) True
2) false
3) true
4) false
5) true
6) true
7) false
8) false
9) false
10) true