Machine Learning Unsupervised Learning 4

Question 1

What is the role of the 'epsilon' parameter in DBSCAN?

Accepted Answer

It defines the maximum radius of a neighborhood around a point

Answer

Epsilon (ε) defines the radius within which DBSCAN searches for neighboring points to determine core points and cluster membership.

Question 2

Which technique can reduce dimensionality while also revealing nonlinear structure in data?

Accepted Answer

UMAP

Answer

UMAP (Uniform Manifold Approximation and Projection) is a nonlinear dimensionality reduction technique that preserves both local and some global structure.

Question 3

What is a key difference between agglomerative and divisive hierarchical clustering?

Accepted Answer

Agglomerative starts with each point as its own cluster and merges; divisive starts with one cluster and splits

Answer

Agglomerative (bottom-up) clustering merges the closest clusters iteratively, while divisive (top-down) starts with all data in one cluster and recursively splits.

Question 4

In the context of anomaly detection, which unsupervised approach assigns anomaly scores based on how easily a point can be isolated?

Accepted Answer

Isolation Forest

Answer

Isolation Forest isolates observations by randomly partitioning data; anomalies are isolated in fewer steps (shorter path lengths) than normal points.

Question 5

What is the 'reconstruction error' in an autoencoder used as a signal for?

Accepted Answer

Detecting anomalies, since unusual inputs have higher reconstruction error

Answer

Autoencoders trained on normal data learn to reconstruct normal inputs well; anomalous inputs result in higher reconstruction error, flagging them as outliers.

Machine Learning Practice Test

Machine Learning Practice Test

Machine Learning Unsupervised Learning 4