Question 16
You are working on a binary classification problem where you need to predict whether an email is spam (1) or not (0). You have trained a machine learning model that produces predicted probabilities for each email being spam. You have two different loss functions to consider: the 0-1 loss and the squared loss.
You have a test dataset with the following true labels and predicted probabilities for a set of emails:
| True label | Predicted probability | |
|---|---|---|
| 1 | 0 | 0.8 |
| 2 | 1 | 0.2 |
| 3 | 0 | 0.6 |
| 4 | 1 | 0.9 |
| 5 | 1 | 0.3 |
For the given data set if Predicted probability is greater than 0.5, the predicted label will be 1 and 0 otherwise.
The values of 0-1 loss function will be 3
The values of squared loss will be equals to 2.14
The values of 0-1 loss equals 4.
The values of squared loss will be equals to 3.14