Data Mining II

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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?

Iteration

Initialization

Assignment

Update (correct)

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?

Membership coefficients Signup and view all the answers

What is the purpose of external criteria in cluster analysis?

To evaluate the goodness of clusters Signup and view all the answers

What is the stopping criterion for the K-means algorithm?

When the maximum number of iterations is reached Signup and view all the answers

What is the primary advantage of using Partitioning Around Medoids (PAM) clustering over K-Means?

It is more robust to outliers. Signup and view all the answers

In K-Means clustering, what is recalculated after assigning data points to the nearest centroid?

The centroids. Signup and view all the answers

Which clustering method allows one piece of data to belong to two or more clusters?

Fuzzy C-Means (FCM). Signup and view all the answers

What is used to represent the center of a cluster in Partitioning Around Medoids (PAM) clustering?

An actual data point called a medoid. Signup and view all the answers

What is minimized in Partitioning Around Medoids (PAM) clustering?

A sum of dissimilarities. Signup and view all the answers

What determines the membership degree in Fuzzy C-Means (FCM) clustering?

The Euclidean distance between the data point and the cluster center. Signup and view all the answers

What does the 'k' in the k-means algorithm represent?

The number of clusters Signup and view all the answers

What is the difference between a cluster and a group in data mining?

There is no difference between a cluster and a group Signup and view all the answers

What type of clustering is characterized by each data point belonging exclusively to one cluster?

Hard Clustering Signup and view all the answers

What is the primary goal of clustering in data mining?

To find the underlying patterns in the data Signup and view all the answers

What is the characteristic of partitional clustering?

Data is divided into non-overlapping subsets Signup and view all the answers

What is the purpose of clustering in data mining?

To identify the underlying patterns in the data Signup and view all the answers

What is the key difference between hard clustering and fuzzy clustering?

In hard clustering, each data point belongs exclusively to one cluster, whereas in fuzzy clustering, each data point can belong to multiple clusters with varying degrees of membership. Signup and view all the answers

What is the primary goal of hierarchical clustering?

To build a hierarchy of clusters. Signup and view all the answers

What is the advantage of hierarchical agglomerative clustering?

It can find smaller clusters in the data that other clustering methods might miss. Signup and view all the answers

What is the main difference between hierarchical agglomerative clustering and hierarchical divisive clustering?

Hierarchical agglomerative clustering is a 'bottom-up' approach, whereas hierarchical divisive clustering is a 'top-down' approach. Signup and view all the answers

What is a characteristic of fuzzy clustering that makes it particularly useful in certain situations?

Its flexibility in dealing with unclear or well-defined boundaries between clusters. Signup and view all the answers

What is the primary output of cluster analysis?

A grouping of data points into clusters based on their similarities and differences. Signup and view all the answers

What is the key characteristic of K-Means clustering that distinguishes it from hierarchical clustering?

It partitions the data into distinct, non-overlapping clusters. Signup and view all the answers

What is the primary goal of clustering in data mining?

To find underlying patterns or groups in the data Signup and view all the answers

How does the initial selection of centroids affect the outcome of K-Means clustering?

The randomly selected initial centroids can lead to different clustering results. Signup and view all the answers

What is the key difference between hard clustering and fuzzy clustering?

In hard clustering, each data point belongs exclusively to one cluster, whereas in fuzzy clustering, a data point can belong to multiple clusters with varying degrees of membership. Signup and view all the answers

What is the primary advantage of using Fuzzy C-Means clustering over hard clustering methods?

It allows for partial membership of a data point in multiple clusters. Signup and view all the answers

How does Partitioning Around Medoids (PAM) clustering differ from K-Means clustering?

PAM uses medoids (actual data points) to represent cluster centers, whereas K-Means uses mean values. Signup and view all the answers

What is the purpose of the k-means algorithm in data mining?

To divide data into non-overlapping subsets (clusters) such that each data object is in exactly one subset. Signup and view all the answers

What is the main purpose of cluster analysis in data mining?

To group similar data points into clusters based on their characteristics. Signup and view all the answers

What is the main characteristic of hierarchical clustering?

Not specified in the given text Signup and view all the answers

What is the role of cluster analysis in data mining?

To identify patterns or groups in the data and understand the underlying structure Signup and view all the answers

What is the key difference between hard clustering and fuzzy clustering?

Hard clustering assigns each data point to a single cluster, while fuzzy clustering allows for partial membership. Signup and view all the answers

What is the difference between a cluster and a group in data mining?

Not specified in the given text Signup and view all the answers

Data Mining II

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Questions and Answers

What is the main purpose of the K-means algorithm?

What is the term for the process of re-calculating the centroids of clusters?

What is used to measure the distance between a data point and a centroid?

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 stopping criterion for the K-means algorithm?

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?

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 minimized in Partitioning Around Medoids (PAM) clustering?

What determines the membership degree in Fuzzy C-Means (FCM) clustering?

What does the 'k' in the k-means algorithm represent?

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 is the primary goal of clustering in data mining?

What is the characteristic of partitional clustering?

What is the purpose of clustering in data mining?

What is the key difference between hard clustering and fuzzy clustering?

What is the primary goal of hierarchical clustering?

What is the advantage of hierarchical agglomerative 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 the primary output of cluster analysis?

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?

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 primary advantage of using Fuzzy C-Means clustering over hard clustering methods?

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 main purpose of cluster analysis in data mining?

What is the main characteristic of hierarchical clustering?

What is the role of cluster analysis in data mining?

What is the key difference between hard clustering and fuzzy clustering?

What is the difference between a cluster and a group in data mining?

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