In-sample fit full model
It is coding time again, which means coming back to the exercise dataset defaultData.
You now want to know how your model performs by calculating the accuracy. In order to do so, you first need a confusion matrix.
Take the logitModelFull, first. The model is already specified and lives in your environment.
Cet exercice fait partie du cours
Machine Learning for Marketing Analytics in R
Instructions
- Use
predict()to receive a probability of each customer defaulting on their payment. - In order to construct the confusion matrix use the function
confusion.matrix()fromSDMTools. Note thatSDMToolscannot be downloaded from CRAN anymore. So if you want to practice at your home computer you can install the package by usingremotes::install_version("SDMTools", "1.1-221.2")which will install the version ofSDMToolsthat is used at this course. - Choose a common threshold of 0.5.
- Calculate the accuracy using the confusion matrix.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Make predictions using the full Model
defaultData$predFull <- predict(logitModelFull, type = ___, na.action = ___)
# Construct the in-sample confusion matrix
confMatrixModelFull <- confusion.matrix(defaultData$___,defaultData$___, threshold = ___)
confMatrixModelFull
# Calculate the accuracy for the full Model
accuracyFull <- sum(diag(___)) / ___(___)
accuracyFull