Assignment - 3 | Super Survey Maker

A classroom with students learning about Bayesian classifiers and machine learning concepts, with charts and diagrams on the board, modern and engaging style.

Understanding Bayesian Classifiers

Test your knowledge on Bayesian classifiers and their role in machine learning with this engaging quiz! Answer questions ranging from classification tasks to different learning methods, and gain deeper insights into the fundamentals of data analysis.

Key Topics Covered:

Classification Techniques
Naive Bayes Algorithm
Learning Methods: Supervised vs Unsupervised
Practical Applications in Telecommunications and Earthquake Prediction

10 Questions2 MinutesCreated by LearningTree42

Bayesian classifiers is

A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory.

Any mechanism employed by a learning system to constrain the search space of a hypothesis

An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation.

None of these

Classification is

A measure of the accuracy, of the classification of a concept that is given by a certain theory

The task of assigning a classification to a set of examples

A subdivision of a set of examples into a number of classes

None of these

What is the use of Naive Bayes Algorithm?

Generate mining models

Estimating the probability of a class value during classification and prediction

To make decisions for reporting.

Both a and b

Classification task referred to

A subdivision of a set of examples into a number of classes

The task of assigning a classification to a set of examples

A measure of the accuracy, of the classification of a concept that is given by a certain theory

None of these

The problem of finding hidden structure in unlabeled data is called...

Unsupervised learning

Reinforcement learning

Supervised learning

Data Learning

Task of inferring a model from labeled training data is called

Reinforcement learning

Unsupervised learning

Supervised learning

None of these

Some telecommunication company wants to segment their customers into distinct groups in order to send appropriate subscription offers, this is an example of ...

Supervised learning

Seriation

Unsupervised learning

Data extraction

You are given data about seismic activity in Japan, and you want to predict a magnitude of the next earthquake, this is in an example of ...

Unsupervised learning

Dimensionality reduction

Seriation

Supervised learning

Algorithm is

It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations

Computational procedure that takes some value as input and produces some value as output

Science of making machines performs tasks that would require intelligence when performed by humans

None of these

Assignment - 3

Understanding Bayesian Classifiers

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