Advanced Unsupervised ML Challenge Quiz

Probe deep into unsupervised algorithms and techniques with demanding questions on core ML concepts.

#clustering#unsupervised learning#anomaly detection#t-SNE#GMM#K-means#DBSCAN#PCA

Total Questions

8

Difficulty Level

hard

Progress

0/0

0%

Quiz Questions

Answer all questions below and test your knowledge.

1
In K-means++, how are initial centroids selected to improve convergence?
Question 1
2
In DBSCAN, what distinguishes a core point from a border point?
Question 2
3
What does Principal Component Analysis (PCA) primarily maximize?
Question 3
4
t-SNE is particularly effective at preserving which aspect of data structure?
Question 4
5
In Gaussian Mixture Models (GMM), which algorithm is typically used for parameter estimation?
Question 5
6
In agglomerative hierarchical clustering, complete linkage measures distance as:
Question 6
7
Autoencoders perform unsupervised learning primarily by:
Question 7
8
Isolation Forest detects anomalies by:
Question 8