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  1. #1
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    linear regression practice




    I wanted to check over my answers based on these 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


    and any explanations to 2 & 10 would also be helpful. Thanks!

  2. #2
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    Re: linear regression practice

    If someone can please help me out on this, I'd be grateful. Thanks!

  3. #3
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    Re: linear regression practice


    I posted some reply to these 2 questions, but waiting on someone to assist me then I can reply to you. Thanks

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