The algorithms we will discuss are based on a fairly wide variety of fundamental learning techniques such as information theory, gradient descent, euclidean distance, Bayes’ theorem, and a number of other techniques.Which of those do you suppose is used by the following algorithms: Artificial Neural Networks?Bayes' theoreminformation theorygradient descenteuclidean distanceCheck It!MLDecision Trees?Bayes' theoreminformation theorygradient descenteuclidean distance K Nearest Neighbor?O Bayes' theoremO information theorygradient descenteuclidean distance

Naive Baye's is learned using the k nearest neighbors of the test instance as the training data and…

Answered: K Nearest Neighbor? O Bayes' theorem O…

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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The algorithms we will discuss are based on a fairly wide variety of fundamental learning techniques such as information theory, gradient descent, euclidean distance, Bayes’ theorem, and a number of other techniques.
Which of those do you suppose is used by the following algorithms:

Artificial Neural Networks?
Bayes' theorem
information theory
gradient descent
euclidean distance
Check It!
ML
Decision Trees?
Bayes' theorem
information theory
gradient descent
euclidean distance

K Nearest Neighbor?
O Bayes' theorem
O information theory
gradient descent
euclidean distance

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