Consider the following data: 0.1 0.2 0.3 0.4 0.5 y -1 1 -1 1 1 Assume that three iterations of the bagging algorithm are run on this dataset with the first sample being x=0.1, x30.1 x=0.3, x-0.4,...

3.

Extracted text: Consider the following data: 0.1 0.2 0.3 0.4 0.5 y -1 1 -1 1 1 Assume that three iterations of the bagging algorithm are run on this dataset with the first sample being x=0.1, x30.1 x=0.3, x-0.4, x-0.4, the second sample being x-0.1, x=0.2, x-0.2, x-0.2 x=0.4 and the third sample being x-0.1. x-0.1, x-0.2. x=0.3, x-0.5 The classifier for each sample is a decision stump which takes the form of a constant c such that > c is assigned one class and xs cis assigned the other class. The constant c is chosen according to the criterion of maximizing information gain. Find the predictions made by the bagging classifier on the given dataset.