Advanced Data Analytics and Machine Learning Quiz

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What is the main difference between supervised and unsupervised machine learning methods?

Supervised methods do not require human experts, while unsupervised methods need guidance from experts.

Supervised methods rely on human experts to process data, while unsupervised methods autonomously discover patterns in data. (correct)

Supervised methods are used for clustering, while unsupervised methods focus on regression.

Supervised methods are more complex than unsupervised methods.

In machine learning, what type of problem involves estimating the mathematical relationship between continuous variables?

Association Problems

Classification Problems

Regression Problems (correct)

Clustering Problems

What is the main goal of a classification problem in machine learning?

To identify continuous variables

To discover patterns autonomously

To estimate to which predefined class a sample belongs (correct)

To compute mathematical relationships

What is the primary function of a boundary line in a classification problem?

To classify new examples based on the line's location and shape Signup and view all the answers

Which machine learning method requires data sets that have been processed by human experts?

Regression Signup and view all the answers

In machine learning, what does an unsupervised method like Clustering do?

Autonomously discovers patterns in data Signup and view all the answers

What is the mode of a data sample?

The value that occurs the most often Signup and view all the answers

What is a measure of how far each value in a dataset is from the mean?

Standard deviation Signup and view all the answers

What does the range statistic describe?

The spread of values in the sample Signup and view all the answers

Which central tendency measure leaves out an important part of the distribution?

Mean Signup and view all the answers

What does the standard deviation measure in a data set?

Variability of values from the mean Signup and view all the answers

In machine learning, what is the purpose of detecting patterns in data?

To uncover patterns for future data predictions Signup and view all the answers

What is the main purpose of Principal Component Analysis (PCA)?

To convert correlated variables into linearly uncorrelated variables Signup and view all the answers

Which machine learning method uses Bayes’ theorem with strong independence assumptions between features?

Naive Bayes classifiers Signup and view all the answers

What is the objective of Singular Value Decomposition (SVD) in linear algebra?

To factorize a real complex matrix into three matrices Signup and view all the answers

What does Independent Component Analysis (ICA) focus on revealing?

Hidden factors underlying random variables Signup and view all the answers

In what scenario would Ordinary Least Squares Regression be used?

To fit a straight line through a set of points Signup and view all the answers

Which statistical technique is characterized by converting correlated variables into linearly uncorrelated variables?

Singular Value Decomposition (SVD) Signup and view all the answers