XGBoost模型转sql语句工具包
现在是大数据量的时代，我们开发的模型要应用在特别大的待预测集上，使用单机的python，需要预测2、3天，甚至更久，中途很有可能中断。因此需要通过分布式的方式来预测。这个工具包就是实现了将训练好的python模型，转换成sql语句。将生成的sql语句可以放到大数据环境中进行分布式执行预测，能比单机的python预测快好几个量级
思想碰撞
| 微信 | 微信公众号 |
|---|---|
 |
 |
| 干饭人 | 魔都数据干饭人 |
仓库地址：https://github.com/ZhengRyan/xgboost2sql
环境准备
可以不用单独创建虚拟环境，因为对包的依赖没有版本要求
xgboost2sql 安装
pip install（pip安装）
pip install xgboost2sql # to install
pip install -U xgboost2sql # to upgrade
Source code install（源码安装）
python setup.py install
运行样例
###【注意：：：核验对比python模型预测出来的结果和sql语句预测出来的结果是否一致请查看教程代码】"https://github.com/ZhengRyan/xgboost2sql/examples/tutorial_code.ipynb"
- 导入相关依赖
import xgboost as xgb
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from xgboost2sql import XGBoost2Sql
- 训练1个xgboost二分类模型
X, y = make_classification(n_samples=10000,
n_features=10,
n_informative=3,
n_redundant=2,
n_repeated=0,
n_classes=2,
weights=[0.7, 0.3],
flip_y=0.1,
random_state=1024)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1024)
###训练模型
model = xgb.XGBClassifier(n_estimators=3)
model.fit(X_train, y_train)
#xgb.to_graphviz(model)
- 使用xgboost2sql工具包将模型转换成的sql语句
xgb2sql = XGBoost2Sql()
sql_str = xgb2sql.transform(model)
- 将sql语句保存
xgb2sql.save()
- 将sql语句打印出来
print(sql_str)
select key,1 / (1 + exp(-(tree_1_score + tree_2_score + tree_3_score)+(-0.0))) as score
from (
select key,
--tree1
case when (f9<-1.64164519 or f9 is null) then
case when (f3<-4.19117069 or f3 is null) then
case when (f2<-1.31743848 or f2 is null) then
-0.150000006
else
-0.544186056
end
else
case when (f3<1.23432565 or f3 is null) then
case when (f7<-2.55682254 or f7 is null) then
-0.200000018
else
case when (f5<0.154983491 or f5 is null) then
0.544721723
else
case when (f3<0.697217584 or f3 is null) then
-0.150000006
else
0.333333373
end
end
end
else
case when (f5<-1.0218116 or f5 is null) then
case when (f0<-0.60882163 or f0 is null) then
case when (f2<0.26019755 or f2 is null) then
0.0666666701
else
-0.300000012
end
else
-0.520000041
end
else
0.333333373
end
end
end
else
case when (f9<1.60392439 or f9 is null) then
case when (f3<0.572542191 or f3 is null) then
case when (f5<0.653370142 or f5 is null) then
case when (f7<-0.765973091 or f7 is null) then
case when (f3<-0.432390809 or f3 is null) then
0.204000011
else
-0.485454559
end
else
case when (f3<-1.20459461 or f3 is null) then
-0.5104478
else
0.441509455
end
end
else
case when (f7<0.133017987 or f7 is null) then
case when (f8<0.320554674 or f8 is null) then
-0.290322572
else
0.368339777
end
else
case when (f8<-0.211985052 or f8 is null) then
0.504000008
else
-0.525648415
end
end
end
else
case when (f7<2.22314501 or f7 is null) then
case when (f8<-0.00532855326 or f8 is null) then
case when (f8<-0.204920739 or f8 is null) then
-0.533991575
else
-0.200000018
end
else
0.428571463
end
else
case when (f3<1.33772755 or f3 is null) then
case when (f0<-0.975171864 or f0 is null) then
0.163636371
else
0.51818186
end
else
-0
end
end
end
else
case when (f3<1.77943277 or f3 is null) then
case when (f7<-0.469875157 or f7 is null) then
case when (f3<-0.536645889 or f3 is null) then
case when (f9<1.89841866 or f9 is null) then
-0
else
0.333333373
end
else
case when (f4<-2.43660188 or f4 is null) then
0.150000006
else
0.551020443
end
end
else
case when (f1<-0.0788691565 or f1 is null) then
0.150000006
else
-0.375
end
end
else
case when (f4<-1.73232496 or f4 is null) then
-0.150000006
else
case when (f6<-1.6080606 or f6 is null) then
-0.150000006
else
case when (f7<-0.259483218 or f7 is null) then
-0.558620751
else
-0.300000012
end
end
end
end
end
end
as tree_1_score,
--tree2
case when (f9<-1.64164519 or f9 is null) then
case when (f3<-4.19117069 or f3 is null) then
case when (f0<0.942570388 or f0 is null) then
-0.432453066
else
-0.128291652
end
else
case when (f3<1.23432565 or f3 is null) then
case when (f7<-2.55682254 or f7 is null) then
-0.167702854
else
case when (f5<0.154983491 or f5 is null) then
case when (f1<2.19985676 or f1 is null) then
0.41752997
else
0.115944751
end
else
0.115584135
end
end
else
case when (f5<-1.0218116 or f5 is null) then
case when (f0<-0.60882163 or f0 is null) then
-0.119530827
else
-0.410788596
end
else
0.28256765
end
end
end
else
case when (f9<1.60392439 or f9 is null) then
case when (f3<0.460727394 or f3 is null) then
case when (f5<0.653370142 or f5 is null) then
case when (f7<-0.933565617 or f7 is null) then
case when (f3<-0.572475374 or f3 is null) then
0.182491601
else
-0.377898693
end
else
case when (f3<-1.20459461 or f3 is null) then
-0.392539263
else
0.352721155
end
end
else
case when (f7<0.207098693 or f7 is null) then
case when (f8<0.498489976 or f8 is null) then
-0.193351224
else
0.29298231
end
else
case when (f8<-0.117464997 or f8 is null) then
0.400667101
else
-0.402199954
end
end
end
else
case when (f7<1.98268723 or f7 is null) then
case when (f8<-0.00532855326 or f8 is null) then
case when (f7<1.36281848 or f7 is null) then
-0.408002198
else
-0.236123681
end
else
case when (f5<1.14038813 or f5 is null) then
0.404326111
else
-0.110877581
end
end
else
case when (f3<1.56952488 or f3 is null) then
case when (f5<2.14646816 or f5 is null) then
0.409404457
else
0.0696995854
end
else
-0.32059738
end
end
end
else
case when (f3<1.77943277 or f3 is null) then
case when (f7<-0.469875157 or f7 is null) then
case when (f3<-0.536645889 or f3 is null) then
case when (f9<1.89841866 or f9 is null) then
-0
else
0.28256765
end
else
0.419863999
end
else
case when (f3<0.444227457 or f3 is null) then
-0.34664312
else
0.0693304539
end
end
else
case when (f4<-1.10089087 or f4 is null) then
case when (f3<2.3550868 or f3 is null) then
0.0147894565
else
-0.331404865
end
else
-0.421277165
end
end
end
end
as tree_2_score,
--tree3
case when (f9<-1.64164519 or f9 is null) then
case when (f3<-4.19117069 or f3 is null) then
case when (f4<-1.30126143 or f4 is null) then
-0.0772174299
else
-0.374165356
end
else
case when (f3<1.23432565 or f3 is null) then
case when (f7<-2.55682254 or f7 is null) then
-0.142005175
else
case when (f5<0.154983491 or f5 is null) then
case when (f7<3.59379435 or f7 is null) then
0.352122813
else
0.132789165
end
else
0.0924336985
end
end
else
case when (f5<-1.0218116 or f5 is null) then
case when (f0<-0.60882163 or f0 is null) then
-0.0954768136
else
-0.351594836
end
else
0.245992288
end
end
end
else
case when (f9<1.60392439 or f9 is null) then
case when (f3<0.347133756 or f3 is null) then
case when (f5<0.661561131 or f5 is null) then
case when (f7<-0.933565617 or f7 is null) then
case when (f3<-0.472413659 or f3 is null) then
0.116336405
else
-0.313245147
end
else
case when (f3<-1.5402329 or f3 is null) then
-0.352897167
else
0.311400592
end
end
else
case when (f7<0.275665522 or f7 is null) then
case when (f8<0.403402805 or f8 is null) then
-0.292606086
else
0.220064178
end
else
case when (f8<-0.0442957953 or f8 is null) then
0.350784421
else
-0.336107522
end
end
end
else
case when (f7<1.77503061 or f7 is null) then
case when (f8<0.196157426 or f8 is null) then
case when (f7<1.36281848 or f7 is null) then
-0.3376683
else
-0.0711223111
end
else
case when (f7<-0.661211252 or f7 is null) then
0.434363276
else
-0.219307661
end
end
else
case when (f3<1.37940335 or f3 is null) then
case when (f6<1.34894884 or f6 is null) then
0.367155522
else
0.124757253
end
else
-0.293739736
end
end
end
else
case when (f3<1.77943277 or f3 is null) then
case when (f7<-0.469875157 or f7 is null) then
case when (f3<-0.536645889 or f3 is null) then
case when (f9<1.89841866 or f9 is null) then
-0
else
0.245992288
end
else
case when (f0<1.60565615 or f0 is null) then
0.357973605
else
0.193993196
end
end
else
case when (f9<1.89456153 or f9 is null) then
-0.276471078
else
0.111896731
end
end
else
case when (f1<1.35706067 or f1 is null) then
case when (f4<-1.10089087 or f4 is null) then
case when (f3<2.3550868 or f3 is null) then
0.0119848112
else
-0.284813672
end
else
-0.376859784
end
else
case when (f2<-0.25748384 or f2 is null) then
0.0723158419
else
-0.253415495
end
end
end
end
end
as tree_3_score
from data_table)
1 maintainer
Metadata
1 maintainer
Release files for xgboost2sql 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| xgboost2sql-0.1.1.tar.gz | 17.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| xgboost2sql-0.1.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 26.1 kB
Release files / xgboost2sql-0.1.1.tar.gz
| Download URL | xgboost2sql-0.1.1.tar.gz |
|---|---|
| Size | 17.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/4.0.2 CPython/3.7.2
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Release files / xgboost2sql-0.1.1-py2.py3-none-any.whl
| Download URL | xgboost2sql-0.1.1-py2.py3-none-any.whl |
|---|---|
| Size | 9.0 kB |
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|
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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