Clustering Flashcards
1
Q
- Introduce the unsupervised learning problem
- What is clustering (definition)?
- What are the difficulties of clustering?
- Model for clustering
- What are the 2 Classes of Algorithms for Clustering?
A
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2
Q
Cost Minimization Clustering
- Approach and assumptions.
- What are the 3 main objective functions?
A
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3
Q
- What is a brute force algorithm to sole K-means? What is its problem?
- Lloyd’s Algorthm, its convergence criteria, its complexity, after how many iterations it stops?
- kmeans++
A
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4
Q
Linkage-Based Clustering
- How the algorithm works?
- What are the 2 parameters that it needs?
- What is a dendrogram? What it represents?
- How can we choose the number k of clusters? What is and how Silhouette works?
- Clustering for Predictions.
A
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