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- W4296443246 abstract "We evaluate SDGs India Score (composite score) and the 15 SDGs score by 28 states in India. The method is a machine learning regression, and the results are interpreted by SHAP values. The target variable is SDGs India score (composite score) calculated by NITI (National Institution for Transforming India) Aayog and the predictors are 15 SDGs Indexes scores except for SDGs14:LifeBelowWater and SDGs17:Partnership. The advantage of the SHAP approach is that we can evaluate which predictor’s contribution to the target is higher than others. From the SHAP analysis, we found that the most important factor in 2018 was SDGs3:Health and in 2020 that was SDGs1:NoPoverty." @default.
- W4296443246 created "2022-09-20" @default.
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- W4296443246 date "2022-08-09" @default.
- W4296443246 modified "2023-09-28" @default.
- W4296443246 title "SDGs India Index Analysis using SHAP" @default.
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- W4296443246 doi "https://doi.org/10.1109/ies55876.2022.9888439" @default.
- W4296443246 hasPublicationYear "2022" @default.
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