I have a simple calculation question.
(我有一个简单的计算问题。)
I have a trouble to calculate 'Contribution of feature'. (我在计算“功能贡献”时遇到麻烦。)
Model : LightGBM (Python 3.7) Objective : Classification
(型号:LightGBM(Python 3.7)目标:分类)
My shap values are below.
(我的shap值如下。)
( There are 6 features ) ((有6个功能))
LIMIT_BAL |
(LIMIT_BAL |)
SEX | (性|)
EDUCATION | (教育|)
MARRIAGE | (婚姻|)
AGE | (年龄|)
PAY_0 | (PAY_0 |)
-0.344984 |
(-0.344984 |)
-0.033723 | (-0.033723 |)
0.012379 | (0.012379 |)
0.019236 | (0.019236 |)
-0.013549 | (-0.013549 |)
0.706214 | (0.706214 |)
And Model's Prediction and Base value are below.
(模型的预测值和基础值如下。)
prediction : 27.62% base value : 19.29% (预测:27.62%基础值:19.29%)
Prediction |
(预测|)
Base Value | (基本价值)
Prediction - Base Value | (预测-基本值|)
0.276298 |
(0.276298 |)
0.192927 | (0.192927 |)
0.083371 | (0.083371 |)
I want to calculate individual feature's contribution.
(我要计算单个功能的贡献。)
Question) How can I calculate the contribution? (问题)我如何计算捐款?)
I thought below solution.
(我认为下面的解决方案。)
For example,
(例如,)
'Contribution of PAY_0' = (shap value(PAY_0) / sum of shap values) * (prediction - base value)
('PAY_0的贡献'=(shap值(PAY_0)/ sap值之和)*(预测-基本值))
= 0.706214/(-0.344984 + -0.033723 + 0.012379 + 0.019236 + -0.013549 + 0.706214 ) * 0.0083371
(= 0.706214 /(-0.344984 + -0.033723 + 0.012379 + 0.019236 + -0.013549 + 0.706214)* 0.0083371)
= 0.170378 = 17.03%
(= 0.170378 = 17.03%)
I don't know the right way.
(我不知道正确的方法。)
Thanks. (谢谢。)
ask by J L translate from so 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…