ML-Clustering

Which type of machine learning is clustering categorized under?

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• Semi-supervised learning

What is the primary objective of clustering in machine learning?

• Predicting future values of a target variable

• Classifying data into predefined categories

• Discovering underlying patterns and grouping similar data points together

• Maximizing the accuracy of a predictive model

Which of the following clustering algorithms is based on centroids and aims to minimize the within-cluster sum of squares?

• K-Means

• DBSCAN

• Hierarchical clustering

• Mean-Shift

In K-Means clustering, how is the initial placement of cluster centroids determined?

• Randomly

• Based on the first data points in the dataset

• By the mean value of all data points

• Using the median value of the dataset

Which clustering algorithm is density-based and can identify noise/outliers as well as form non-spherical clusters?

• K-Means

• Hierarchical clustering

• DBSCAN

• Agglomerative clustering

The silhouette score is a metric used to evaluate the quality of clustering. It ranges from:

• -1 to 0

• 0 to 1

• -1 to 1

• 1 to 100

Agglomerative and divisive are two main approaches in which type of clustering?

• Hierarchical clustering

• Density-based clustering

• Partition-based clustering

• Prototype-based clustering

Which clustering algorithm utilizes a "dendrogram" to represent the hierarchy of merged clusters?

• K-Means

• DBSCAN

• Hierarchical clustering

• Mean-Shift

The number of clusters in K-Means clustering is determined by:

• The mean value of the dataset

• The median value of the dataset

• The user-specified value of 'k'

• The variance of the dataset

Which clustering algorithm starts with each data point as its own cluster and merges the closest clusters in each iteration?

• K-Means

• Hierarchical clustering

• DBSCAN

• Mean-Shift