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