All shap values were NA.

[hyr13579]

library(fastshap) train_data <- as.data.frame(train_data) shap <- explain( rf, X = as.data.frame(train_data), nsim = 1, adjust = FALSE, shap_only = TRUE, pred_wrapper = function(model,newdata){ as.data.frame(predict(model,newdata) ) %>% pull(1) } )

When I run the above code, all the shap values I get are NA.There are a lot of warniings. Warnings ( ) 1: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 2: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 3: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 4: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 5: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 6: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 7: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 8: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 9: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 10: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 11: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 12: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 13: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 14: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 15: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 16: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 17: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 18: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 19: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 20: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 21: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 22: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 23: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 24: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 25: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 26: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 27: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 28: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 29: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 30: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 31: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 32: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 33: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 34: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 35: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 36: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 37: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 38: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 39: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 40: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 41: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 42: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 43: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 44: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 45: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 46: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 47: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 48: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 49: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors 50: In Ops.factor(pred_wrapper(object, newdata = B[[1L]]), ... : ‘-’ not meaningful for factors

[hyr13579]

rf is a Multiclass classification model，Can you tell me how to calculate the shap value? Thank you vary much！

[bgreenwell]

Hi @hyr13579 thank you for posting an issue. However, without a reproducible example to run on my end, I can’t do much to help diagnose your issue. Please post a fully reproducible example and consider using the reprex package.

[hyr13579]

Thank you. I changed the code. It worked. shap<- explain(rf, X = as.data.frame(train_data), nsim = 100, pred_wrapper = function(model, newdata){ as.data.frame(predict(model, newdata, type = "prob")) %>% pull(1)}) When I run the above code, all the shap values I get are number.

[bgreenwell]

Glad you got it to work!