Output - Aster Analytics

Teradata AsterĀ® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
dita:mapPath
uce1497542673292.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1022
lifecycle
previous
Product Category
Software

The function returns a success message and creates 3 output tables.

ConfusionMatrix Example Output Message
message
Success !

The result has been outputted to tables:

"confusionmatrix_output_1", "confusionmatrix_output_2" and "confusionmatrix_output_3"

The query below returns the output shown in the following table:

SELECT * FROM confusionmatrix_output_1 ORDER BY 1;

Three output tables are created by the function query. The following output table provides the confusion matrix (also known as contingency table):

ConfusionMatrix Example Output Table confusionmatrix_output_1
observation/predict setosa versicolor virginica
setosa 10 0 0
versicolor 0 9 3
virginica 0 1 7

The query below returns the output shown in the following table:

SELECT * FROM confusionmatrix_output_2 ORDER BY 1;

The following table contains statistical values:

ConfusionMatrix Example Output Table confusionmatrix_output_2
key value
95% CI (0.6928, 0.9624)
Accuracy 0.8667
Kappa 0.8
Mcnemar Test P-Value NA
Null Error Rate 0.4
P-Value [Acc > NIR] 0

The query below returns the output shown in the following table:

SELECT * FROM confusionmatrix_output_3 ORDER BY 1;

The following table contains accuracy/error measures like sensitivity and specificity for each class.

ConfusionMatrix Example Output Table confusionmatrix_output_3
measure virginica setosa versicolor
Balanced Accuracy 0.8693 1 0.8472
Detection Prevalence 0.3333 0.3333 0.3333
Detection Rate 0.2333 0.3333 0.3
Neg Pred Value 0.95 1 0.85
Pos Pred Value 0.7 1 0.9
Prevalence 0.2667 0.3333 0.4
Sensitivity 0.875 1 0.75
Specificity 0.8636 1 0.9444