Model <- train(Movement~., tuneLength = 5, data = Database, method = "rpart", trControl = trainControl(method = "cv", number = 10, savePredictions = "final", classProbs = T)) confusionMatrix(Model$pred[order(Model $pred$rowIndex),2], Database$Movement)
After running my code for my multiclass database (11 different classes), I receive the following results for Overall Statistics:
Accuracy : 0.5808 95% CI : (0.5649, 0.5965) No Information Rate : 0.1681 P-Value [Acc > NIR] : < 2.2e-16 Kappa : 0.5301 Mcnemar's Test P-Value : NA
but I do have more performance measures for each class
> Statistics by Class: > Class AccelerationAg Class: AccelerationNon Class: BackGround > Sensitivity 0.91929825 0.00000000 0.83685801 > Specificity 0.91368541 1.00000000 0.98676640 > Pos Pred Value 0.46289753 NaN 0.85758514 > Neg Pred Value 0.99290342 0.92907801 0.98450057 > Precision 0.46289753 NA 0.85758514 > Recall 0.91929825 0.00000000 0.83685801 > F1 0.61574618 NA 0.84709480 > Prevalence 0.07486210 0.07092199 0.08694510 > Detection Rate 0.06882059 0.00000000 0.07276070 > Detection Prevalence 0.14867350 0.00000000 0.08484371 > Balanced Accuracy 0.91649183 0.50000000 0.91181220
I am wondering how can I calculate other performance measures such as precision, recall, F1, sensitivity, etc for the overall database not by each class such as the accuracy and Kappa that I have already calculated for in the overall statistics. I mean, the confusionmatrix function is calculating everything that I need but by each class and I want those statistics for the overall (whole) database. For instance, as you can see above, the accuracy of my model is 0.5808 which indicates the overall accuracy of my database for prediction. I want to calculate the overall Recall, F1, Precision, Sensitivity, Specificity, etc. of my entire database not by class.
I do appreciate your help in advance,