Documentation: Statistics/Machine Learning

Real-Time Decomposition of Time Series

The STD2 operator is capable of performing online decomposition of a time series. More specifically, the STD2 operator is capable of ingesting a time series...

Introduction to the Spark MLLib Toolkit in IBM Streams V4.1

Ankit Pasricha is the team lead of the IBM Streams Toolkit development team. In his presentation, Ankit will introduce the new Spark MLLib Toolkit that...

Getting Started with the Spark MLLib Toolkit

Apache Spark is a fast general purpose clustering system that is well suited for machine learning algorithms. This guide will demonstrate how you can...

Predicting the Future in a Streams Application

Time series forecasting is a very broad subject. The ability to forecast future values is applicable in areas such as sales forecasting, stock market analysis...

Support for SPSS Analytics Toolkit in Bluemix Streaming Analytics Service

The Bluemix Streaming Analytics Service provides support for the SPSS Analytics Toolkit. With this support, your Streams application can perform in-stream predictive scoring using...

Anomaly Detection in Streams

This article demonstrates how to use the AnomalyDetector operator, which is capable of detecting anomalous subsequences in a streaming time series.

SPSS Analytics Toolkit Lab

Leverage the analytics of SPSS in real-time using the IBM SPSS Analytics Toolkit for Streams.

Bandpass and bandstop filters using the DSPFilter operator

The DSPFilter operator implements a butterworth filter and can be used to isolate frequencies in a time series. For example, a low pass filter can...

R Toolkit Lab

Integrate R Statistical Computing with streams.

IBM SPSS and Streams FAQ

Learn about SPSS and Streams Integration. Why should you? What you need? And tutorial information.