Regularization is introduced in class as a numeric term that can be incorporated into a loss function. This is straightforward for algorithms such as neural networks that seek to optimize a numeric loss function. Here, explain possible ways regularization can be used to fine tune other types of algorithms, specifically decision trees and naive Bayes classifiers.

What questions about an audience should be asked during presentation preparation? check all that apply. what does the audience already know about the topic? how will multimedia tools inspire the audience? is the information interesting and engaging? how will this information affect the presentation? will the audience change the message’s purpose? what is likely to interest the audience?