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An overview of the four main approaches to predictive analytics

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This infographic provides an overview of the four main families of approaches to predictive analytics. Prediction encompasses applications that aim to estimate or predict the values of a key target field. Segmentation refers to techniques such as cluster analysis which attempt to find the most ‘naturally occurring” groups within a dataset. Association modelling discovers groups …

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

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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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Expert insight: Inna Yordanova, Senior Researcher at IPSE

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Inna Yordanova is Senior Researcher at IPSE – the Association of Independent Professionals and the Self-Employed. IPSE is the largest organisation representing freelancers and self-employed people. Its 78,000 members are freelancers, contractors, consultants and other self-employed people from all sectors of the economy. Lorna: Can you start off then just by telling me a little …

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Expert insight – Adam O’Shaughnessy, SBD Automotive

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Through independent research, evaluation and strategic consulting support, SBD Automotive helps vehicle manufacturers and their partners create autonomous, more secure and better connected cars. Adam O’Shaughnessy is a Senior Specialist – Connected Car.  Lorna: Can you tell me a little bit about your background and how you’ve come to be working with data and statistics …

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Expert insight: Rob Woods, Analytics Solution Architect/Data Scientist, Watson FSS

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Rob Woods has worked in the analytics industry for over 20 years. He’s currently an Analytics Solutions Architect working on IBM’s Watson FSS suite of products. All views here are his own and not IBM’s. Describe your own background and how you came to be working with statistics / data / analytics I started as …

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