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| {{Infobox nodebasic
| | #Redirect [[SHAP]] |
| |nodename=SHAP
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| |nodeimage=SHAP.png
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| |icon=SHAP.svg
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| |simpleicon=SHAP_Pure.svg
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| |developer=Dev.Team-DPS
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| |productionstate={{图标文件|Win}} / {{图标文件|W10}} Win10及以上可用
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| |productionstatedesc=在[[Update:DecisionLinnc 1.0.0.8|V1.0]]部署
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| |nodeenglishname=[[Has english name::SHAP]]
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| |abbreviation=[[Has abbreviation::SHAP]]
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| |funcmaincategory=机器学习
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| |funcsubcategory=[[Eva Lv1 Cat::模型评估]]
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| |nodecategory=数据挖掘
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| |nodeinterpretor=R
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| |nodeshortdescription=<p>SHAP（SHapley Additive exPlanations）是一种用于解释机器学习模型预测的算法和框架。它基于博弈论中的Shapley值概念，并将其应用于解释预测模型中各个特征对最终预测结果的贡献程度。</p>
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| |nodeinputnumber=2
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| |nodeoutputnumber=2
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| |nodeloopsupport=否
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| |nodeifswitchsupport=否
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| |nodeavailableplotlist=DistributionHeatMap;DoubleCoordinateLinePlot;HeatBeesPlot;HeatPointPlot;BarHorizontalPlot
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| |nodeavailabletablelist=Table_For_Downstream
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| |nodeconfiguration=VariableList
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| |nodeinputports=WorkFlow-Control ➤;Transfer-Table ■
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| |nodeoutputports=WorkFlow-Control ➤;Transfer-Table ■
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| |statsapewikiurl=https://wiki.statsape.com/SHAP
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| |previousnode=[[机器学习基础绘图节点]]
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| |nextnode=[[多模型评估节点]]
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| }}
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| {{Navplate AlgorithmNodeList}}
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| [[Category:模型评估]]
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