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Machine Learning Algorithms – DenStream Clustering

SAP HANA SPS11 introduces two machine learning algorithms that can be used in streaming projects: Adaptive Hoeffding Tree and DenStream Clustering. Integrating machine learning algorithms with smart data streaming combines supervised learning and unsupervised learning such that one can efficiently train data models in real-time.

This tutorial will walk you through a demo of the DenStream Clustering machine learning algorithm.

Summary of DenStream Clustering:

  • Analyzes continuous streams of data in real-time
  • Forms data clusters of any shape and handles outliers
    • There are core-micro-clusters and outlier-micro-clusters
  • Changes the weight of clusters over time (depending on the weight, outlier-micro-clusters can become core-micro-clusters)
  • Updates so only necessary information is kept

Applications of DenStream Clustering:

  • Analyzing data streams from sensors on Internet of Things (IoT) devices
  • Identifying patterns in spending money (helps detect fraud)
  • Grouping information for search engines
  • Mapping demographics of consumers to types of purchases

View the tutorial here: Machine Learning Algorithms - DenStream Clustering

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