Machine Learning Algorithms – Hoeffding Tree

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