July 2018
Beginner to intermediate
376 pages
9h 1m
English
When using the bagging method, we combine the result of many decision trees and produce a single output/prediction by taking a majority count. Under a different sampling mechanism, the results had been combined to produce a single prediction for the random forests. Under a sequential error reduction method for decision trees, the boosting method also provides improved answers. Although we are dealing with uncertain data, which involves probabilities, we don't intend to have methodologies that give results out of a black box and behave without consistent solutions. A theory should explain the working and we need an assurance that the results will be consistent and there is no black magic about it. Arbitrary and uncertain ...