SPSS Predictive Extensions allow you to add functionality to SPSS Statistics and Modeler by connecting to APIs, plotting geospatial data, adding external data sources, processing advanced statistical techniques, and much more. Learn more about using extensions and how to develop your own. Continue reading Learn About SPSS Predictive Extensions
In the new release of IBM SPSS Modeler 17.1 we introduced integration with Apache Spark. In this post I will explain more about this integration and why it is so powerful. SPSS democratizes analytics, extending benefits to users who do not want to program. Access to a broader library of analytic algorithms delivers solutions to... Continue reading Spark integration in SPSS Modeler 17.1
Today we are launching our first free training at the Big Data University about 'Predictive Modeling Fundamentals I'. In this training you will learn the basics of IBM SPSS Modeler. We will solve the Kaggle Challenge: Titanic: Machine Learning from Disaster from Data Preparation to Deployment. Continue reading Learn SPSS at the Big Data University!
A great way to explain the analytics maturity and value curve is to use the idea of descriptive, predictive, and prescriptive analytics. But how does one go from just predictive into the realm of prescriptive analytics? What’s the secret to success at that level? That’s where IBM Analytical Decision Management comes into play. Continue reading The Power of Decisions: Analytical Decision Management
IBM Analytics Services have released a new implementation method for Data Mining/Predictive Analytics projects called Analytics Solutions Unified Method for Data Mining/Predictive Analytics (also known as ASUM-DM) which is a refined and extended CRISP-DM. Continue reading Have you seen ASUM-DM?
To close these series of posts about the new algorithms of IBM SPSS Modeler 17.1, today is the turn of Tree-AS. The Tree-AS node can be used with data in a distributed environment to build CHAID decision trees using chi-square statistics to identify optimal splits Continue reading Run decision trees on Big Data
Today I'm going to introduce two new algorithms of IBM SPSS Modeler 17.1: Generalized Linear Engine (GLE) and Linear-AS. GLE provides a variety of statistical models such as linear regression for normally distributed responses, logistic models for binary data, log linear models for count data any many more through its very general model formulation.... Continue reading Generalized Linear Engine and Linear AS
Today let's introduce Linear Support Vector Machine (LSVM), another new algorithm included with IBM SPSS Modeler 17.1. Continue reading Linear Support Vector Machine in Modeler 17.1
The Random Trees node can be used with data in a distributed environment to build an ensemble model that consists of multiple decision trees. Continue reading Random Trees algorithm in SPSS Modeler 17.1
We are excited to announce our newly designed SPSS Community website. The new design makes it easy to find the latest content and answers for everything related to SPSS. Read more about the community enhancements. Continue reading Welcome to the Redesigned SPSS Community