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
