library(cheem)
library(e1071)
library(DALEX)
-
-## Classification setup
-X <- chocolates[, 5:14]
-Y <- chocolates$Type
-clas <- chocolates$Type
-
-## Model and predict
-choc_svm_fit <- svm(
- formula = Y ~ ., data = data.frame(Y, X),
- type = 'C-classification', kernel = 'linear', probability = TRUE)
-chocolates_svm_pred <- predict(choc_svm_fit, data.frame(Y, X))
-
-## SHAP via DALEX, versatile but slow
-choc_svm_exp <- explain(choc_svm_fit, data = X, y = Y,
- label = "Chocolates, svm")
-## Note that cheem expects a full [n, p] attribution space
-chocolates_svm_shap <- matrix(NA, nrow(X), ncol(X)) ## init a df of the same structure
-tictoc::tic("choc svm DALEX shap")
-sapply(1:nrow(X), function(i){
- pps <- predict_parts_shap(choc_svm_exp, new_observation = X[i, ])
- ## Keep just the [n, p] local explanations
- chocolates_svm_shap[i, ] <<- tapply(
- pps$contribution, pps$variable, mean, na.rm = TRUE) %>% as.vector()
-})
-chocolates_svm_shap <- as.data.frame(chocolates_svm_shap)
-tictoc::toc() ## ~35-40 sec for me
+set.seed(135)
+
+## Classification setup
+X <- chocolates[, 5:14]
+Y <- chocolates$Type
+clas <- chocolates$Type
+
+## Model and predict
+choc_svm_fit <- svm(
+ formula = Y ~ ., data = data.frame(Y, X),
+ type = 'C-classification', kernel = 'linear', probability = TRUE)
+chocolates_svm_pred <- predict(choc_svm_fit, data.frame(Y, X))
+
+## SHAP via DALEX, versatile but slow
+choc_svm_exp <- explain(choc_svm_fit, data = X, y = Y,
+ label = "Chocolates, svm")
+## Note that cheem expects a full [n, p] attribution space
+## Shap takes about ~30-40 sec for me
+chocolates_svm_shap <- matrix(NA, nrow(X), ncol(X)) ## init a df of the same structure
+sapply(1:nrow(X), function(i){
+ pps <- predict_parts_shap(choc_svm_exp, new_observation = X[i, ])
+ ## Keep just the [n, p] local explanations
+ chocolates_svm_shap[i, ] <<- tapply(
+ pps$contribution, pps$variable, mean, na.rm = TRUE) %>% as.vector()
+})
+chocolates_svm_shap <- as.data.frame(chocolates_svm_shap)
if(F){ ## Don't accidentally save
save(chocolates_svm_pred, file = "./data/chocolates_svm_pred.rda")
@@ -126,16 +126,16 @@