18 Questions
What is the main goal of clustering?
To find distinct groups in a data set that are similar within each group
Which type of learning are clustering methods categorized under?
Unsupervised learning
How are points within the same cluster expected to be?
As similar as possible
What is one common application of clustering in business?
Market Segmentation
Which clustering technique involves finding centroids and updating the cluster assignments iteratively?
K-Means Clustering
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
What is the key property of the clusters in K-Means Clustering?
The clusters are non-overlapping
What is the objective of K-Means Clustering?
To minimize the within-cluster variation
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
What is the optimization problem that defines K-Means Clustering?
Minimize the sum of squared Euclidean distances between observations and their assigned cluster centroids
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
What is one of the strengths of K-Means Clustering mentioned in the text?
It is a simple iterative method
What is the main objective of K-means clustering?
Classifying observations based on features
In K-means clustering, what is done at the end of the 1st iteration?
Determining which points belong to which clusters
What criterion is used to determine when to stop the K-means clustering process?
Minimum movement of cluster centers
Which property must sets 𝐶1, ..., 𝐶𝑘 satisfy in K-means clustering?
Disjointness: no observation can belong to multiple clusters
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
Which step in K-means clustering involves recalculating the cluster centers based on the points assigned to each cluster?
Finding the new cluster centers
Test your understanding of clustering techniques such as K-Means Clustering and Hierarchical Clustering. Explore the concept of clustering as an unsupervised method to group similar observations in a data set.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
