559 search results for "register"

New Webinar this Wednesday: Using survival analysis for marketing attribution

July 15, 2013
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This Wednesday at 11AM Eastern Time, Revolution Analytics UK Business Services Director Andrie DeVries will present a new webinar, Using Survival Analysis for Marketing Attribution. This webinar will focus on a new application of survival analysis (more traditionally used for life sciences application) to the domain of marketing: A central question in advertising is how to measure the effectiveness...

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Fun with Fremont Bridge Bicyclists

June 27, 2013
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Fun with Fremont Bridge Bicyclists

Given the title of this post and its proximity to the Solstice, you will be disappointed to know that I am not writing about naked bicyclists. I apologize for any false hope I may have instilled in you.On October 11th, 2012, the city of Seattle, WA beg...

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Time Is on My Side – A Small Example for Text Analytics on a Stream

June 23, 2013
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Time Is on My Side – A Small Example for Text Analytics on a Stream

Introduction and Background While my last posting was about recommendation in the context of Location Based Social Networks there are also other interesting topics regarding the analysis of unstructured data. The most established one is probably Text Analytics/Mining focusing on all sorts of text data.For me, coming from spatial analysis, these topic is relatively new but I couldn’t help noticing...

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GRNN and PNN

June 23, 2013
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GRNN and PNN

From the technical prospective, people usually would choose GRNN (general regression neural network) to do the function approximation for the continuous response variable and use PNN (probabilistic neural network) for pattern recognition / classification problems with categorical outcomes. However, from the practical standpoint, it is often not necessary to draw a fine line between GRNN

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Prototyping A General Regression Neural Network with SAS

June 22, 2013
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Prototyping A General Regression Neural Network with SAS

Last time when I read the paper “A General Regression Neural Network” by Donald Specht, it was exactly 10 years ago when I was in the graduate school. After reading again this week, I decided to code it out with SAS macros and make this excellent idea available for the SAS community. The prototype of

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Upcoming Rcpp talk in Sydney

June 20, 2013
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The Sydney Users of R Forum (SURF) will be hosting me for a talk on July 10. The focus will be Rcpp for R and C++ integration, and the intent is to have this be really applied with lots of motivating examples. Organizers Louise and Eugene were able...

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Huge interest in next LondonR user group meeting

June 20, 2013
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The next LondonR meeting takes place on the 16 July and registrations have already exceeded 200. Presentations at the meeting will be made by Rich Pugh of Mango Solutions, Andrie de Vries of Revolution Analytics and Hadley Wickham of RStudio. All places for a  pre-meeting workshop with Hadley Wickham were snapped up within 2 days of announcing the details. More information...

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Compiling R 3.0.1 with MKL support

June 19, 2013
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Compiling R 3.0.1 with MKL support

Before you begin, be aware that there is others excellent posts about the issue, as: 1. Compiling 64-bit R 2.10.1 with MKL in Linux 2. Speeding up R with Intel’s Math Kernel Library (MKL) 3. Performance benefits of linking R to multithreaded math libraries 4. Using MKL-Linked R in Eclipse But, as recently i faced some problems to The post Compiling...

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An R package for Smith-Wilson yield curves

June 19, 2013
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An R package for Smith-Wilson yield curves

Yield Curve fitting - the Smith-Wilson method Yield Curve fitting - the Smith-Wilson method This article illustrates the R package SmithWilsonYieldCurve, and provides some additional background on yield curve fitting. The method implemented in the package fits a curve to interest rate market...

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General Regression Neural Network with R

June 16, 2013
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General Regression Neural Network with R

Similar to the back propagation neural network, the general regression neural network (GRNN) is also a good tool for the function approximation in the modeling toolbox. Proposed by Specht in 1991, GRNN has advantages of instant training and easy tuning. A GRNN would be formed instantly with just a 1-pass training with the development data.

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