What is clustering in SAP BI-RA-PA - SAP Predictive Analytics?

SAP Term: clustering

• Component: BI-RA-PA

• Component Name: SAP Predictive Analytics

• Description: The type of predictive analysis performed by a clustering model in Automated Analytics where observations are grouped into clusters. Clustering can be supervised, where a target variable is selected, or unsupervised, where no target variable is selected.

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• Key Concepts: 
  Clustering is a type of unsupervised machine learning algorithm used in SAP Predictive Analytics. It is used to group data points into clusters based on their similarity. Clusters are formed by grouping data points that are close together in terms of their features. The goal of clustering is to identify natural groupings in the data and to understand the underlying structure of the data. 
  
  How to use it: 
  Clustering can be used to identify customer segments, detect outliers, and find patterns in the data. To use clustering, you need to define the number of clusters you want to create and the features you want to use for clustering. You can then use a clustering algorithm such as K-means or hierarchical clustering to group the data points into clusters. 
  
  Tips & Tricks: 
  When using clustering, it is important to choose the right number of clusters and features for your data. You should also consider using different clustering algorithms to see which one gives the best results. Additionally, you should evaluate the quality of your clusters by looking at metrics such as silhouette scores or Dunn indices. 
  
  Related Information: 
  Clustering is closely related to other unsupervised machine learning algorithms such as principal component analysis (PCA) and hierarchical clustering. Additionally, clustering can be used in conjunction with supervised machine learning algorithms such as classification and regression.