18 Questions
What is the main difference between supervised and unsupervised machine learning methods?
Supervised methods rely on human experts to process data, while unsupervised methods autonomously discover patterns in data.
In machine learning, what type of problem involves estimating the mathematical relationship between continuous variables?
Regression Problems
What is the main goal of a classification problem in machine learning?
To estimate to which predefined class a sample belongs
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
Which machine learning method requires data sets that have been processed by human experts?
Regression
In machine learning, what does an unsupervised method like Clustering do?
Autonomously discovers patterns in data
What is the mode of a data sample?
The value that occurs the most often
What is a measure of how far each value in a dataset is from the mean?
Standard deviation
What does the range statistic describe?
The spread of values in the sample
Which central tendency measure leaves out an important part of the distribution?
Mean
What does the standard deviation measure in a data set?
Variability of values from the mean
In machine learning, what is the purpose of detecting patterns in data?
To uncover patterns for future data predictions
What is the main purpose of Principal Component Analysis (PCA)?
To convert correlated variables into linearly uncorrelated variables
Which machine learning method uses Bayes’ theorem with strong independence assumptions between features?
Naive Bayes classifiers
What is the objective of Singular Value Decomposition (SVD) in linear algebra?
To factorize a real complex matrix into three matrices
What does Independent Component Analysis (ICA) focus on revealing?
Hidden factors underlying random variables
In what scenario would Ordinary Least Squares Regression be used?
To fit a straight line through a set of points
Which statistical technique is characterized by converting correlated variables into linearly uncorrelated variables?
Singular Value Decomposition (SVD)
Test your knowledge on advanced data analytics, machine learning, and inferential analysis commonly used in Big Data. Learn about detecting patterns in data, predicting future data, and making decisions under uncertainty.
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