7.00.02 - Input - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Release Date
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)

This example uses the patient_pca_input data set and the variables age, bmi, bloodpressure, glucose, cigarettes, insulin, and hdl to predict the number of strokes for a patient.

The following statement creates the table pca_health_ev2 from a query that conducts a principal component analysis on the other seven variables:

CREATE TABLE pca_health_ev2 DISTRIBUTE BY REPLICATION AS
  SELECT * FROM pca_reduce (
    ON pca_map (
      ON pca_scaled
      TargetColumns ('age', 'bmi', 'bloodpressure', 'glucose',
                     'cigarettes', 'insulin', 'hdl')
    ) PARTITION BY 1
  ) ORDER BY component_rank;

The preceding query uses the same process as query in the PCA example.

The following query returns the table pca_health_ev2:

SELECT * FROM pca_health_ev2;

Because strokes is the response variable, pca_health_ev2 has no strokes column; otherwise, pca_health_ev2 is the same as the output table of the PCA example, pca_health_ev_scaled.

PCAPlot Example Input Table pca_health_ev2 (Columns 1-5)
component_rank age bmi bloodpressure glucose
1 0.558383429424359 -0.0605952043265538 0.279191393011342 0.562811446671035
2 -0.250537483690061 0.614686329749836 -0.258383085318548 -0.0474790977051386
3 -0.0911563605166551 -0.141748695621042 0.251924555111245 -0.220162314985357
4 -0.0965156342595097 0.203200180598669 0.843333872842729 -0.0927285011581401
5 -0.180835348784396 0.599972991222924 0.079755498943645 0.485460834090224
6 0.741419465051456 0.431342026006021 -0.0814633949974965 -0.452698251899937
7 -0.159404889398745 0.105272966756617 0.260029076069335 -0.428148411420131
PCAPlot Example Output Table pca_health_ev2 (Columns 6-9)
cigarettes insulin hdl
0.156485831353259 0.497004566613813 0.135389267935288
0.579594554667163 0.305498725264089 0.247217076371136
0.392249448405349 0.284736376332311 -0.790396081112643
0.201301142840861 -0.36378506450842 0.238164018417497
-0.419465995079716 -0.0691208326400593 -0.42961426285989
-0.0606741267486036 -0.16172687758833 -0.151103636140504
-0.51533240361692 0.644444986031744 0.178058065989532
PCAPlot Example Output Table pca_health_ev2 (Columns 10-13)
sd var_proportion cumulative_var mean
1.42680503704651 0.302942353235311 0.302942353235311 [-2.753353101070388E-16, 8.881784197001253E-17, 1.0658141036401502E-16, -7.993605777301127E-17, -1.3322676295501878E-17, 7.771561172376097E-18, -1.7763568394002505E-17]
1.27431560304133 0.241648847642051 0.544591200877363  
1.01834410187873 0.154319153248689 0.698910354126052  
0.92244700110317 0.126623284203011 0.825533638329062  
0.780266259616559 0.0905975351035737 0.916131173432636  
0.573696298386201 0.0489772980330401 0.965108471465676  
0.484222130587456 0.0348915285343237 1