Confusion matrix
confusion( dataset, pred, rvar, lev = "", cost = 1, margin = 2, train = "All", data_filter = "", envir = parent.frame(), ... )
| dataset | Dataset |
|---|---|
| pred | Predictions or predictors |
| rvar | Response variable |
| lev | The level in the response variable defined as success |
| cost | Cost for each connection (e.g., email or mailing) |
| margin | Margin on each customer purchase |
| train | Use data from training ("Training"), test ("Test"), both ("Both"), or all data ("All") to evaluate model evalbin |
| data_filter | Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000") |
| envir | Environment to extract data from |
| ... | further arguments passed to or from other methods |
A list of results
Confusion matrix and additional metrics to evaluate binary classification models. See https://radiant-rstats.github.io/docs/model/evalbin.html for an example in Radiant
summary.confusion to summarize results
plot.confusion to plot results
data.frame(buy = dvd$buy, pred1 = runif(20000), pred2 = ifelse(dvd$buy == "yes", 1, 0)) %>% confusion(c("pred1", "pred2"), "buy") %>% str()#> List of 9 #> $ dataset : tibble [2 × 19] (S3: tbl_df/tbl/data.frame) #> ..$ Type : chr [1:2] "All" "All" #> ..$ Predictor: chr [1:2] "pred1" "pred2" #> ..$ TP : int [1:2] 2514 5246 #> ..$ FP : int [1:2] 7440 0 #> ..$ TN : int [1:2] 7314 14754 #> ..$ FN : int [1:2] 2732 0 #> ..$ total : int [1:2] 20000 20000 #> ..$ TPR : num [1:2] 0.479 1 #> ..$ TNR : num [1:2] 0.496 1 #> ..$ precision: num [1:2] 0.253 1 #> ..$ Fscore : num [1:2] 0.331 1 #> ..$ RIG : num [1:2] -0.757 1 #> ..$ accuracy : num [1:2] 0.491 1 #> ..$ kappa : num [1:2] -0.0194 1 #> ..$ profit : num [1:2] -4926 5246 #> ..$ index : num [1:2] -0.939 1 #> ..$ ROME : num [1:2] -0.495 1 #> ..$ contact : num [1:2] 0.498 0.262 #> ..$ AUC : num [1:2] 0.511 1 #> $ df_name : chr "." #> $ data_filter: chr "" #> $ train : chr "All" #> $ pred : chr [1:2] "pred1" "pred2" #> $ rvar : chr "buy" #> $ lev : chr "yes" #> $ cost : num 1 #> $ margin : num 2 #> - attr(*, "class")= chr [1:2] "confusion" "list"