University Of Michigan Flint Week 7 Decision Trees and Naive Bayes Analysis

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Week 7 Assignment Instruction

Define the below two classification methods:

  • The decision trees and Naive Bayes.

Elaborate on the theories behind these classifiers. Which one of these classifiers are considered computationally efficient for high dimensional problems and why?


***1) 2-page paper - double spaced. (Does not include the title page and the reference page)

2) APA format

3) 2 scholarly references

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Explanation & Answer

Hi, please see the attached paper. Have a look at it and in case of any edit, please let me know. Otherwise, it is my pleasure to have you as my buddy now and future. Until the next invite, Bye!

Running Head: CLASSIFIERS

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Decision Trees and Naïve Bayes
Name
Institutional Affiliation

CLASSIFIERS

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Decision Trees and Naïve Bayes

Data analytics is an essential part of the understanding of the best way to handle the
interactions between various parties. One of the uses of data classification is in prediction, and
through the use of decision trees and Naïve Bayes, there will be the identification of the
procedure for success in the understanding. The use of these classifiers results in a better
understanding of the situation and the specific data analysis set to be carried out.
Decision Trees
These classifiers revolve around the identification of the specific process of decision
making that ultimately allows for the making of the requisite predictions. It revolves around the
introduction of an input that will allow for the effective prediction of the output, and the specific
decisions that will...


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