SPSS Modeler

Enhancing the power of SPSS Modeler with Regular Expressions

The new RX nodes in IBM SPSS Modeler extend the Visual Data Science approach of SPSS Modeler itself to Regular Expression handling.

In this webinar we demonstrate how you can use the power of REGEX to perform the most typical text handling tasks, without the pain of learning yet another programming language.

Improving predictive models with SPSS Modeler

Using IBM SPSS Modeler, this webinar will demonstrate methods to improve the accuracy of predictive models. It should be noted that most of these approaches are not unique to the SPSS Modeler application and may have relevance for people working with alternative software packages.

Predictive analytics for database marketing using SPSS Modeler

This webinar presents different applications of predictive analytics for database marketers. The aim is to help organisations understand how they can use the information in their marketing database to more effectively acquire new customers as well as to retain those they already have and maximise their value to the organisation.

What’s new in IBM SPSS Modeler 18.3?

SPSS Modeler is a robust data science software for professional analysts and data scientists. The software scales from supporting line-of-business predictive analysis to enterprise-scale implementation.Consisting of IBM SPSS Modeler Desktop 18.3 and IBM SPSS Modeler Server 18.3, SPSS Modeler delivers a robust predictive analytics solution for a holistic approach to predictive analytics. It brings predictive intelligence to decisions made by individuals, …

What’s new in IBM SPSS Modeler 18.3? Read More »

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Using text analytics to get value from unstructured data

What is unstructured data? The data you have access to within your organisation can be broadly sorted into two categories: structured and unstructured. Structured data is quantitative data that can be organised into a format that can neatly be fitted into the fields and columns of relational databases or spreadsheets. Examples might include things like …

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What’s the difference between the various SPSS license types?

IBM SPSS Advanced Analytical Products, including IBM SPSS Statistics and IBM SPSS Modeler, can be implemented and licensed in different ways.  How your organisation invests in, licenses and implements these tools will depend on its requirements.  This page explains and compares the options, or you can watch the quick video guide below. Licence length or term …

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Using SPSS Modeler’s cache_compression setting to speed up your modelling

There are a number of configuration settings associated with IBM SPSS Modeler Server that control its behaviour. The default settings aim to ensure that stream execution will complete successfully even if the host machine is being used by a number of other applications i.e. Modeler Server is trying to be a “good citizen”. However, if …

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6 secrets of building better models part three: feature engineering

Feature Engineering is really just a fancy term for creating new data. Very often we can help an algorithm build better models by preparing the input data in a way that allows it to detect a clearer signal in the often noisy data. In machine learning variables are often referred to as ‘features’, so feature engineering refers to the transformation of variables or the creation of new ones.

6 secrets of building better models part five: meta models

The idea of meta modelling is to build a predictive model using the predictions or scores generated by another model. By adding the predictive scores generated by an initial modelling algorithm to an existing pool of predictor fields, a second algorithm can then exploit these scores in to build a final more accurate model.

6 secrets of building better models part six: split models

Split models or split population modelling is another technique that allows the user to build multiple models which can then be combined to create a single prediction. The idea with split modelling is that if the data represent different populations or contain separate groups that behave in very different ways, assuming that a single model can explain all the inherent variability across these distinct populations might be unreasonable.

Regular Expressions for IBM SPSS Modeler: performance comparison

The Regular Expressions for IBM SPSS Modeler node pack provides 4 nodes that integrate the power and flexibility of regular expression pattern matching into SPSS Modeler. However, some of these capabilities can be supported using the extension nodes built into SPSS Modeler and that begs the question – why buy the Regular Expression nodes? One …

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Introduction to the filter node in SPSS Modeler

Sometimes you may have problems with your data issues not related so much to the values of the data but to the fields themselves, such as awkward field names. The filter node is a really useful tool that offers a bunch of tricks for dealing with awkward fields.

Introduction to the data audit node in SPSS Modeler

The data audit node is a powerful tool you can use to help understand the shape and structure of your data before your analysis begins. You can also make some decisions here regarding how you might want to clean up your data, for example by dealing with missing values or extremes and outliers.

What If Analysis using IBM SPSS Modeler Premium

In this short video Jarlath Quinn demonstrates how to use the powerful simulation tools within IBM SPSS Modeler to perform What If analysis (also known as ‘Scenario Planning’). What if analysis allows business-focused analysts to go beyond simple predictive modelling to evaluate the impact of different choices and scenarios on predicted outcomes.

Predicting asset failure using IBM SPSS Modeler

This video shows you how organisations with substantial capital assets can use IBM SPSS Modeler to predict when asset failure is most likely. Predicting asset failure can prevent problems before they happen and enables organisations to save money, reduce asset downtime and increase efficiency.

Building a predictive model in SPSS Modeler

If you are considering making your first foray into predictive analytics or are interested in seeing the automated capabilities of IBM’s flagship analytical platform, this video will demonstrate the power and ease of building a predictive model in SPSS Modeler.

IBM SPSS Modeler – 8 reasons why it is still brilliant after all these years

IBM SPSS Modeler has been through quite the name changes since it first came onto the market as Clementine in the 1990s. In 1998 it was acquired by SPSS. Controversially, in my mind, SPSS then changed its name to SPSS Modeler (spelled the American way which causes no end of confusion in spell checks or when …

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