Podcast
Questions and Answers
What is the main purpose of the K-means algorithm?
What is the main purpose of the K-means algorithm?
- To select the best number of clusters in a dataset
- To determine the validity indices of clusters
- To calculate the Euclidean distance between data points
- To divide a dataset into non-overlapping subgroups or clusters (correct)
What is the term for the process of re-calculating the centroids of clusters?
What is the term for the process of re-calculating the centroids of clusters?
- Iteration
- Initialization
- Assignment
- Update (correct)
What is used to measure the distance between a data point and a centroid?
What is used to measure the distance between a data point and a centroid?
- Euclidean distance (correct)
- Membership coefficient
- Validity index
- Cluster coefficient
What is the term for the coefficients that determine the degree of membership of a data point in a cluster?
What is the term for the coefficients that determine the degree of membership of a data point in a cluster?
What is the purpose of external criteria in cluster analysis?
What is the purpose of external criteria in cluster analysis?
What is the stopping criterion for the K-means algorithm?
What is the stopping criterion for the K-means algorithm?
What is the primary advantage of using Partitioning Around Medoids (PAM) clustering over K-Means?
What is the primary advantage of using Partitioning Around Medoids (PAM) clustering over K-Means?
In K-Means clustering, what is recalculated after assigning data points to the nearest centroid?
In K-Means clustering, what is recalculated after assigning data points to the nearest centroid?
Which clustering method allows one piece of data to belong to two or more clusters?
Which clustering method allows one piece of data to belong to two or more clusters?
What is used to represent the center of a cluster in Partitioning Around Medoids (PAM) clustering?
What is used to represent the center of a cluster in Partitioning Around Medoids (PAM) clustering?
What is minimized in Partitioning Around Medoids (PAM) clustering?
What is minimized in Partitioning Around Medoids (PAM) clustering?
What determines the membership degree in Fuzzy C-Means (FCM) clustering?
What determines the membership degree in Fuzzy C-Means (FCM) clustering?
What does the 'k' in the k-means algorithm represent?
What does the 'k' in the k-means algorithm represent?
What is the difference between a cluster and a group in data mining?
What is the difference between a cluster and a group in data mining?
What type of clustering is characterized by each data point belonging exclusively to one cluster?
What type of clustering is characterized by each data point belonging exclusively to one cluster?
What is the primary goal of clustering in data mining?
What is the primary goal of clustering in data mining?
What is the characteristic of partitional clustering?
What is the characteristic of partitional clustering?
What is the purpose of clustering in data mining?
What is the purpose of clustering in data mining?
What is the key difference between hard clustering and fuzzy clustering?
What is the key difference between hard clustering and fuzzy clustering?
What is the primary goal of hierarchical clustering?
What is the primary goal of hierarchical clustering?
What is the advantage of hierarchical agglomerative clustering?
What is the advantage of hierarchical agglomerative clustering?
What is the main difference between hierarchical agglomerative clustering and hierarchical divisive clustering?
What is the main difference between hierarchical agglomerative clustering and hierarchical divisive clustering?
What is a characteristic of fuzzy clustering that makes it particularly useful in certain situations?
What is a characteristic of fuzzy clustering that makes it particularly useful in certain situations?
What is the primary output of cluster analysis?
What is the primary output of cluster analysis?
What is the key characteristic of K-Means clustering that distinguishes it from hierarchical clustering?
What is the key characteristic of K-Means clustering that distinguishes it from hierarchical clustering?
What is the primary goal of clustering in data mining?
What is the primary goal of clustering in data mining?
How does the initial selection of centroids affect the outcome of K-Means clustering?
How does the initial selection of centroids affect the outcome of K-Means clustering?
What is the key difference between hard clustering and fuzzy clustering?
What is the key difference between hard clustering and fuzzy clustering?
What is the primary advantage of using Fuzzy C-Means clustering over hard clustering methods?
What is the primary advantage of using Fuzzy C-Means clustering over hard clustering methods?
How does Partitioning Around Medoids (PAM) clustering differ from K-Means clustering?
How does Partitioning Around Medoids (PAM) clustering differ from K-Means clustering?
What is the purpose of the k-means algorithm in data mining?
What is the purpose of the k-means algorithm in data mining?
What is the main purpose of cluster analysis in data mining?
What is the main purpose of cluster analysis in data mining?
What is the main characteristic of hierarchical clustering?
What is the main characteristic of hierarchical clustering?
What is the role of cluster analysis in data mining?
What is the role of cluster analysis in data mining?
What is the key difference between hard clustering and fuzzy clustering?
What is the key difference between hard clustering and fuzzy clustering?
What is the difference between a cluster and a group in data mining?
What is the difference between a cluster and a group in data mining?
