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 Hoeffding Tree machine learning algorithm.

Summary of Hoeffding Tree:

  • Analyzes continuous streams of data in real-time
  • Consists of two parts: Hoeffding Tree Training and Hoeffding Tree Scoring
  • Hoeffding Tree Training:
    • Uses supervised learning to analyze small sample data with known outcomes to choose a tree node splitting attribute
  • Hoeffding Tree Scoring:
    • References trained data
    • Incrementally determines which class / category each new point is

Applications of Hoeffding Tree:

  • Predicting actions of future consumers based on past buyers
  • Monitoring the position of workers for safety (standing, lying on the ground, etc.)
  • Scheduling of employees and use of resources based on the estimations of seasonal workload
  • Determining face and word recognition

View the tutorial here: Machine Learning Algorithms – Hoeffding Tree

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