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

SAP Term: unsupervised clustering

• Component: BI-RA-PA

• Component Name: SAP Predictive Analytics

• Description: The type of cluster analysis performed by a clustering model in Automated Analytics where no target variable is selected.

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• Key Concepts: 
  Unsupervised clustering is a type of data mining technique used in SAP Predictive Analytics. It is used to group data points into clusters based on their similarity. The clusters are formed without any prior knowledge or labels, and the algorithm is used to identify patterns and relationships in the data. 
  
  How to use it: 
  Unsupervised clustering can be used to identify customer segments, detect outliers, and find hidden patterns in the data. To use unsupervised clustering, you need to select the appropriate algorithm and set the parameters for the clustering process. The algorithm will then analyze the data and generate clusters based on the similarity of the data points. 
  
  Tips & Tricks: 
  When using unsupervised clustering, it is important to select an appropriate algorithm and set the parameters correctly. It is also important to evaluate the results of the clustering process to ensure that meaningful clusters have been generated. 
  
  Related Information: 
  Unsupervised clustering is one of many data mining techniques available in SAP Predictive Analytics. Other techniques include supervised learning, association rules, and anomaly detection.