Posts Tagged ‘Predictive Modeling’

Coming from a TM1 background (more business than statistics), it is easy to get stated with modeling once you determine your modeling objective, and Modeler can help with that. IBM SPSS Modeler offers an intuitive interface that will appeal to a wide range of users from the non-technical business user to the statistician, data miner […]

The discovering of relationships within data (between fields) is an important part of any data mining project (in the Crisp-DM methodology, this is described as part of the “Data Understanding” stage). This “relationship discovery” is part of developing a predictive model but is also helpful in answering specific business questions -perhaps even what originally motivated […]

SPSS CLEM is the control Language for Expression Manipulation, which is used to build expressions within SPSS Modeler streams. CLEM is actually used in a number of SPSS “nodes” (among these are the Select and Derive nodes) and you can check the product documentation to see the extended list. CLEM expressions are constructed from: Values, […]

Another interesting feature of SPSS Modeler is its built-in ability to sample data. It is pretty typical to have (in one or more files) hundreds of thousands of records to process, and using complete sets of data during testing can take a huge amount of your time and is inefficient in terms of computer processing […]

Consider the scenario where you have to convert information held in a “categorical field” into a “collection of flag fields” – found in a transactional source. For example, suppose you have a file of transactions that includes (among other fields) a customer identifier (“who”) and a product identifier (“what”).  This file of transactional data indicates […]

Reengineering the Forecasting Process with Predictive Models Forecasts usually start as historical performance which is then reviewed and adjusted based upon anticipated events. More mature forecasting may also incorporate generally accepted business rules “programmed in” to help “drive” the data into a forecast. Over the years I’ve deployed uncountable applications which provide the ability to […]

SunGard has identified ten primary trends that have been shaping the financial services industry’s use of big data in 2012. These trends cover wide-ranging drivers such as predictive analytics, compliance, mobile and globalization. To accompany the list, Neil Palmer and Michael Versace (global research director at IDC Financial Insights) discuss these trends in more detail via webcast. Below is SunGard’s […]