Which of the following is NOT a clustering algorithm, commonly used in Unsupervised Learning?a.Random Forestb.DBSCANc.K-Meansd.Hierarchical Clustering

1. Break Down the Problem

We need to identify which option listed is not a clustering algorithm within the context of Unsupervised Learning.

2. Relevant Concepts

• Clustering Algorithms: Common clustering algorithms include K-Means, DBSCAN, and Hierarchical Clustering.
• Unsupervised Learning: This involves learning patterns from unlabelled data.

3. Analysis and Detail

1. Random Forest: This is primarily a supervised learning algorithm used for classification and regression tasks, not for clustering.
2. DBSCAN: This stands for Density-Based Spatial Clustering of Applications with Noise. It's a clustering algorithm that groups together points that are closely packed together.
3. K-Means: This is a well-known clustering algorithm that partitions data into K distinct clusters based on distance to the centroid.
4. Hierarchical Clustering: This is a method of cluster analysis that seeks to build a hierarchy of clusters.

4. Verify and Summarize

Among the options provided, Random Forest is the only algorithm that does not belong to the category of clustering algorithms commonly used in unsupervised learning.

Final Answer

a. Random Forest is NOT a clustering algorithm commonly used in Unsupervised Learning.