7.00.02 - Output - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)
Last Update
2018-04-17

This query returns the following table:

SELECT * FROM pcr1;
PCAPlot Example Output Table pcr1
pid strokes principal_component_1 principal_component_2 principal_component_3
3 0.795410174399195 0.195110284571174 -1.17825238356938 -1.04290585569861
6 -0.0331420905999665 -1.02505176519817 -1.2375999732885 0.257874309966306
8 1.3477783510653 -1.98240922334734 0.159007920294922 -0.494890984515023
11 -0.30932617893302 -1.00884248343362 -0.597930103709463 0.301060051568942
13 1.3477783510653 1.091766978011 -1.16460787259922 -2.17662153529429
16 0.519226086066141 -1.93840477808707 -0.0623801090526926 -0.936238178663301
19 -1.13787844393218 -1.14924574475721 1.7169286389402 0.588543776698959
21 -0.585510267266074 0.144749031593665 1.56905010871958 0.52484021423205
24 1.07159426273225 -0.65879037722031 0.120392373582135 0.915771821734939
2 -1.13787844393218 -1.27086507768138 -0.0479281470754135 0.732287038132982
5 -1.41406253226524 0.308542873080395 2.70938975527651 -3.04594531776213
7 -0.585510267266074 -1.61658595260732 0.71226267926454 0.957505372598163
10 0.795410174399195 0.723400299704323 -3.73227341951059 0.574740342890179
15 -0.0331420905999665 1.50953494759911 -0.643862090689209 -0.235674114998759
18 0.519226086066141 -1.13206482033264 -0.946451923900274 0.153459109295282
20 -1.13787844393218 -0.447229210945602 0.669928830364427 0.306483821831369
23 0.519226086066141 0.956038577607332 -0.649328546941474 -0.825039826251437
1 0.243041997733087 0.830295227878681 0.204892485389732 -0.205590257682169
4 -1.13787844393218 -1.57924450867301 0.122683543836927 1.080304476172
9 -0.861694355599128 3.08093421824054 0.794495651675079 1.2894482577175
12 1.3477783510653 0.0232126330286096 -0.372098909138089 -0.867874315202764
14 -1.13787844393218 3.77988804114414 0.62813244997315 0.744457517669959
17 -1.41406253226524 0.121200199618048 2.08086374773324 0.786060284561275
22 0.795410174399195 -0.215566553625099 -0.989679133035365 -0.169609921563112
25 1.62396243939836 1.25962718383174 0.134364427459238 0.787553912561683

The example has reduced the original data set from 25 observations with 7 predictors to 25 observations with 3 predictors (the 3 score variables principal_component_1, principal_component_2, and principal_component_3).