We present how to build random forest models from streaming data. This is achieved by training, predicting and adapting the model in real-time with evolving data streams. The implementation is on the open source library StreamDM, built on top of Apache Spark.
Heitor Murilo Gomes
I am currently a senior research fellow at the University of Waikato in the machine learning group. My main research area is Machine Learning, specially Evolving Data Streams, Concept Drift, Ensemble methods and Big Data Streams. I contribute to MOA (Java), StreamDM (Spark Streaming) and scikit-multiflow (Python) open data stream mining projects.