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
dita:ditavalPath
AA-notempfilter_pdf_output.ditaval
dita:id
B700-1022
lifecycle
previous
Product Category
Software
XGBoost_Drive Example 2 Output Message
message
Input table:"iris_train"
Parameters: 
Number of boosting iterations : 10
Number of boosted trees : 2
Number of total trees (all subtrees): 60
Prediction Type : CLASSIFICATION
LossFunction : SOFTMAX
Regularization : 1.0
Shrinkage : 0.1
MaxDepth : 10
MinNodeSize : 1
Variance : 0.0
Seed : 1
ColumnSubSampling Features: 5
XGBoost model created in table "xgboost_model"

The following query returns the output shown in the following table. For simplicity, the last two output columns show only the first 30 characters of each value.

SELECT tree_id, iter, class_num, cast (tree AS VARCHAR(30)),
  cast(region_prediction AS varchar(30))
  FROM xgboost_model ORDER BY 1,2,3;
XGBoost_Drive Example 2 Output Model Table xgboost_model
tree_id iter class_num cast(tree as character varying(30)) cast(region_prediction as character varying(30))
-1 -1 -1 {"classifier":"CLASSIFICATION"  
0 1 0 {"sum_":-1.5999999974924961E-6 {"1280":0.1142857,"64":0.06153
0 1 1 {"sum_":-1.6000000001570314E-6 {"256":-0.030769233,"192":0.06
0 1 2 {"sum_":-1.5999999958271616E-6 {"128":-0.030769233,"1792":0.1
0 2 0 {"sum_":0.003643369999999313," {"73":0.057703428,"11":0.03549
0 2 1 {"sum_":-0.04117511999999829," {"66":-0.030396814,"67":-0.030
0 2 2 {"sum_":0.037531760000000025," {"512":-0.029956799,"513":-0.0
0 3 0 {"sum_":0.03708117999999927,"s {"192":-0.017302776,"193":-0.0
0 3 1 {"sum_":-0.08834119000000096," {"66":-0.029580407,"67":-0.029
0 3 2 {"sum_":0.051260599999997325," {"640":-0.029278005,"641":-0.0
0 4 0 {"sum_":0.04687535000000198,"s {"896":-0.016578998,"897":-0.0
0 4 1 {"sum_":-0.0678746099999995,"s {"130":-0.028774833,"131":-0.0
0 4 2 {"sum_":0.020999030000000363," {"12":0.032886423,"15":0.05637
0 5 0 {"sum_":0.03755811000000081,"s {"64":0.052787222,"65":0.05319
0 5 1 {"sum_":-0.034850230000002924, {"128":-0.027421547,"129":-0.0
0 5 2 {"sum_":-0.0027087800000022977 {"12":0.03218222,"16":-0.01639
0 6 0 {"sum_":0.04646400000000178,"s {"256":0.05095709,"257":0.0306
0 6 1 {"sum_":-0.007737959999998878, {"128":-0.02659559,"258":-0.01
0 6 2 {"sum_":-0.03872571000000247," {"16":-0.016017327,"19":-0.016
0 7 0 {"sum_":0.06499833999999843,"s {"128":0.049224634,"259":0.030
0 7 1 {"sum_":0.00869173000000012,"s {"268":-0.026575554,"269":-0.0
0 7 2 {"sum_":-0.07369031999999831," {"14":0.048336674,"16":-0.0156
0 8 0 {"sum_":0.08203318000000381,"s {"896":-0.015550173,"897":-0.0
0 8 1 {"sum_":0.030948259999999894," {"9":-0.01614619,"141":-0.0150
0 8 2 {"sum_":-0.11298213999999918," {"1280":-0.015266706,"641":-0.
0 9 0 {"sum_":0.08537154000000086,"s {"1792":-0.015166406,"1793":-0
0 9 1 {"sum_":0.06144761000000026,"s {"9":-0.015856637,"142":-0.014
0 9 2 {"sum_":-0.1468193699999989,"s {"388":0.030198824,"389":0.030
0 10 0 {"sum_":0.08631954000000114,"s {"896":-0.014946807,"897":-0.0
0 10 1 {"sum_":0.08354898999999982,"s {"9":-0.015570814,"142":-0.014
0 10 2 {"sum_":-0.1698681799999997,"s {"388":0.029783908,"389":0.029
1 1 0 {"sum_":-1.5999999974924961E-6 {"1280":0.1142857,"64":0.06153
1 1 1 {"sum_":-1.6000000001570314E-6 {"256":-0.030769233,"192":0.06
... ... ... ... ...