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, x=0.1 x-0.3, x-0.4, x-04, the second sample being x-0.1, x-0.2, x-0.2, x-0.2 x0.4 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 x 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.

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, x=0.1 x-0.3, x-0.4, x-04, the second sample being x-0.1, x-0.2, x-0.2, x-0.2 x0.4 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 x 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.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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