MLA Final Quiz: Clustering Algorithms and Unsupervised Learning
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Questions and Answers

Which algorithm is sensitive to the initialization of cluster centroids?

  • DBSCAN
  • Hierarchical clustering
  • K-means (correct)
  • Decision Trees

Which algorithm is used for feature selection?

  • Hierarchical clustering
  • K-means
  • Decision Trees (correct)
  • DBSCAN

Which algorithm is used for imputing missing values?

  • DBSCAN
  • K-means (correct)
  • Hierarchical clustering
  • Decision Trees

Which algorithm is prone to the curse of dimensionality?

<p>t-SNE (D)</p> Signup and view all the answers

Which algorithm uses a dendrogram to represent the hierarchy of clusters?

<p>Hierarchical clustering (A)</p> Signup and view all the answers

Which algorithm is computationally expensive for large datasets?

<p>t-SNE (A)</p> Signup and view all the answers

Which algorithm is used for reducing the number of features?

<p>PCA (B)</p> Signup and view all the answers

Which algorithm has a parameter called 'min_samples'?

<p>DBSCAN (B)</p> Signup and view all the answers

Which algorithm can handle non-convex clusters?

<p>DBSCAN (C)</p> Signup and view all the answers

Which algorithm is based on the concept of proximity?

<p>DBSCAN (C)</p> Signup and view all the answers

What is the main drawback of K-means clustering?

<p>It requires a predetermined number of clusters (A)</p> Signup and view all the answers

Which algorithm is sensitive to the choice of initial cluster centroids?

<p>K-means (A)</p> Signup and view all the answers

What is the primary use of DBSCAN?

<p>Clustering (A)</p> Signup and view all the answers

Which algorithm is not a clustering algorithm?

<p>Decision Trees (B)</p> Signup and view all the answers

What problem is t-SNE designed to solve?

<p>Dimensionality reduction (B)</p> Signup and view all the answers

In which type of learning is the number of clusters not pre-specified?

<p>Unsupervised learning (C)</p> Signup and view all the answers

Which algorithm is sensitive to outliers?

<p>DBSCAN (C)</p> Signup and view all the answers

What does the perplexity parameter control in t-SNE?

<p>Local neighborhood size (C)</p> Signup and view all the answers

In Random Forest, what is the main purpose of using Decision Trees?

<p>To reduce variance (D)</p> Signup and view all the answers

Which clustering algorithm is not sensitive to the order of input data points?

<p>DBSCAN (A)</p> Signup and view all the answers

Among the algorithms listed, which one can handle non-linear data effectively?

<p>Decision Trees (C)</p> Signup and view all the answers

What does the 'k' in K-means clustering represent?

<p>Number of clusters (C)</p> Signup and view all the answers

Which algorithm is suitable for visualizing high-dimensional data in lower dimensions?

<p>t-SNE (A)</p> Signup and view all the answers

In Decision Trees, what is the primary purpose of using entropy?

<p>To measure impurity (A)</p> Signup and view all the answers

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