FEM 2063 Data Analytics Chapter 8: Clustering Quiz

Play an AI-generated podcast conversation about this lesson

What is the main goal of clustering?

To predict the outcome of a target variable
To classify data into predefined categories
To find distinct groups in a data set that are similar within each group (correct)
To calculate the mean of the dataset

Which type of learning are clustering methods categorized under?

Reinforcement learning
Supervised learning
Semi-supervised learning
Unsupervised learning (correct)

How are points within the same cluster expected to be?

No similarity required
Randomly assigned
As similar as possible (correct)
As different as possible

What is one common application of clustering in business?

Market Segmentation (B) Signup and view all the answers

Which clustering technique involves finding centroids and updating the cluster assignments iteratively?

K-Means Clustering (A) Signup and view all the answers

In clustering, what does it mean to say points in the same group are 'quite similar'?

Have minimal differences based on a defined similarity measure (D) Signup and view all the answers

What is the key property of the clusters in K-Means Clustering?

The clusters are non-overlapping (B) Signup and view all the answers

What is the objective of K-Means Clustering?

To minimize the within-cluster variation (D) Signup and view all the answers

How is the within-cluster variation W(Ck) defined in K-Means Clustering?

As the sum of squared Euclidean distances between observations in the cluster (B) Signup and view all the answers

What is the optimization problem that defines K-Means Clustering?

Minimize the sum of squared Euclidean distances between observations and their assigned cluster centroids (C) Signup and view all the answers

What is one of the weaknesses of K-Means Clustering mentioned in the text?

It requires the user to specify the number of clusters (K) in advance (A) Signup and view all the answers

What is one of the strengths of K-Means Clustering mentioned in the text?

It is a simple iterative method (D) Signup and view all the answers

What is the main objective of K-means clustering?

Classifying observations based on features (C) Signup and view all the answers

In K-means clustering, what is done at the end of the 1st iteration?

Determining which points belong to which clusters (A) Signup and view all the answers

What criterion is used to determine when to stop the K-means clustering process?

Minimum movement of cluster centers (C) Signup and view all the answers

Which property must sets 𝐶1, ..., 𝐶𝑘 satisfy in K-means clustering?

Disjointness: no observation can belong to multiple clusters (B) Signup and view all the answers

What is the purpose of finding the Euclidean distance between cluster center and each point in K-means clustering?

To update the cluster centers iteratively (D) Signup and view all the answers

Which step in K-means clustering involves recalculating the cluster centers based on the points assigned to each cluster?

Finding the new cluster centers (C) Signup and view all the answers