5.4.5 - Tutorial - Factor Analysis - Teradata Warehouse Miner

Teradata Warehouse Miner User Guide - Volume 3Analytic Functions

Product
Teradata Warehouse Miner
Release Number
5.4.5
Published
February 2018
Language
English (United States)
Last Update
2018-05-04
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In this example, principal components analysis is performed on a correlation matrix for 21 numeric variables. This reduces the variables to 7 factors using a minimum eigenvalue of 1. The Scree Plot supports limiting the number of factors to 7 by showing how the eigenvalues (and thus the explained variance) level off at 7 or above.

  1. Parameterize a Factor Analysis as follows:
    • Available Matrices — Customer_Analysis_Matrix
    • Selected Variables
      • income
      • age
      • years_with_bank
      • nbr_children
      • female
      • single
      • married
      • separated
      • ccacct
      • ckacct
      • svacct
      • avg_cc_bal
      • avg_ck_bal
      • avg_sv_bal
      • avg_cc_tran_amt
      • avg_cc_tran_cnt
      • avg_ck_tran_amt
      • avg_ck_tran_cnt
      • avg_sv_tran_amt
      • avg_sv_tran_cnt
      • cc_rev
    • Analysis Method — Principal Components
    • Matrix Type — Correlation
    • Minimum Eigenvalue — 1
    • Invert signs if majority of matrix values are negative — Enabled
    • Rotation Options — None
    • Factor Variables — Enabled
    • Threshold Percent — 1
    • Long Report — Not enabled
  2. Run the analysis.
  3. Click Results when it completes.

    For this example, the Factor analysis generated the following pages. A single click on each page name populates the Results page with the item.

    Factor Analysis Report
    Number of Variables 21
    Minimum Eigenvalue 1
    Number of Factors 7
    Matrix Type Correlation
    Rotation None
    Execution Summary
    6/20/2004 1:55:02 PM Getting Matrix
    6/20/2004 1:55:02 PM Principal Components Analysis Running...x
    6/20/2004 1:55:02 PM Creating Report
    Eigenvalues
    Factor 1 4.292
    Factor 2 2.497
    Factor 3 1.844
    Factor 4 1.598
    Factor 5 1.446
    Factor 6 1.254
    Factor 7 1.041
    (Factor 8) .971
    (Factor 9) .926
    (Factor 10) .871
    (Factor 11) .741
    (Factor 12) .693
    (Factor 13) .601
    (Factor 14) .504
    (Factor 15) .437
    (Factor 16) .347
    (Factor 17) .34
    (Factor 18) .253
    (Factor 19) .151
    (Factor 20) .123
    (Factor 21) 7.01E-02
    Principal Component Loadings
    Variable Name Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7
    age 0.2876 -0.4711 0.1979 0.2615 0.2975 0.3233 -0.2463
    avg_cc_bal -0.7621 0.0131 0.1628 -0.1438 0.3508 -0.1550 -0.0300
    avg_cc_tran_amt 0.3716 -0.0318 -0.1360 0.0543 -0.1975 0.0100 0.0971
    avg_cc_tran_cnt 0.4704 0.0873 -0.4312 0.5592 -0.0241 0.0133 0.0782
    avg_ck_bal 0.5778 0.0527 -0.0981 -0.4598 0.0735 -0.0123 -0.0542
    avg_ck_tran_amt 0.7698 0.0386 -0.0929 -0.4535 0.2489 0.0585 0.0190
    avg_ck_tran_cnt 0.3127 0.1180 -0.1619 -0.1114 0.5435 0.1845 0.0884
    avg_sv_bal 0.3785 0.3084 0.4893 0.0186 -0.0768 -0.0630 0.0517
    avg_sv_tran_amt 0.4800 0.4351 0.5966 0.1456 -0.0155 0.0272 0.1281
    avg_sv_tran_cnt 0.2042 0.3873 0.4931 0.1144 0.2420 0.0884 -0.0646
    cc_rev 0.8377 -0.0624 -0.1534 0.0691 -0.3800 0.1036 0.0081
    ccacct 0.2025 0.5213 0.4007 0.3021 0.0499 -0.1988 0.1733
    ckacct 0.4007 0.1496 -0.4215 0.5497 0.1127 -0.0818 -0.0086
    female -0.0209 0.1165 -0.1357 0.3119 0.1887 -0.2228 -0.3438
    income 0.6992 -0.2888 0.1353 -0.2987 -0.2684 0.0733 0.0310
    married 0.0595 -0.7702 0.2674 0.2434 0.1945 0.0873 0.2768
    nbr_children 0.2560 -0.4477 0.1238 -0.0895 -0.0739 -0.5642 0.0898
    separated 0.3030 0.0692 0.0545 -0.0666 -0.0796 -0.5089 -0.6425
    single -0.2902 0.7648 -0.3004 -0.2010 -0.2120 0.2527 0.0360
    svacct 0.4365 0.1616 -0.2592 -0.1705 0.6336 -0.1071 0.0318
    years_with_bank 0.0362 -0.0966 0.2120 0.0543 -0.0668 0.5507 -0.5299