Input
- InputTable: iris_train, created in DecisionTree Example 1
SQL Call
SELECT * FROM XGBoost ( ON iris_train AS InputTable OUT TABLE OutputTable (xgboost_model2) USING ResponseColumn ('species') NumericInputs ('sepal_length','sepal_width','petal_length','petal_width') LossFunction ('softmax') IterNum (10) MaxDepth (10) MinNodeSize (1) RegularizationLambda (1) ShrinkageFactor (0.1) IDColumn ('id') NumBoostedTrees (2) ) AS dt;
Output
message |
---|
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 specified in OutputTable argument |
This query returns the following table:
SELECT tree_id, iter, class_num, cast (tree AS VARCHAR(30)), cast(region_prediction AS varchar(30)) FROM xgboost_model2 ORDER BY 1,2,3;
For simplicity, the last two output columns show only the first 30 characters of each value.
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 |
... | ... | ... | ... | ... |