335 search results for "evaluation"

CFP: the 11th Australasian Data Mining Conference (AusDM 2013), submission due 15 July

April 3, 2013
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CFP: the 11th Australasian Data Mining Conference (AusDM 2013), submission due 15 July

********************************************************************* The 11th Australasian Data Mining Conference (AusDM 2013) Canberra, Australia, 13-15 November 2013, http://ausdm13.togaware.com Join us on LinkedIn: http://www.linkedin.com/groups/AusDM-4907891 ********************************************************************* Data mining, the art and science of intelligent analysis of (usually large) data sets for meaningful (and previously unknown) … Continue reading →

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Lots of data != "Big Data"

March 28, 2013
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Lots of data != "Big Data"

by Joseph Rickert When talking with data scientists and analysts — who are working with large scale data analytics platforms such as Hadoop — about the best way to do some sophisticated modeling task it is not uncommon for someone to say, "We have all of the data. Why not just use it all?" This sort of comment often...

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Writing a MS-Word document using R (with as little overhead as possible)

March 24, 2013
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Writing a MS-Word document using R (with as little overhead as possible)

The problem: producing a Word (.docx) file of a statistical report created in R, with as little overhead as possible. The solution: combining R+knitr+rmarkdown+pander+pandoc (it is easier than it is spelled). If you get what this post is about, just …Read more »

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Review of Mathematica 9 and R-link

March 18, 2013
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VIDEO TRANSCRIPT: Hello, this is Matt Asher from StatisticsBlog.com. I’m going to be reviewing Mathematica 9, from Wolfram Research. In particular, I’ll be focusing on using it with R and to do Monte Carlo simulations and other statistical work. You can find a full transcript of this video at my blog, including the source code

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Job advert

March 12, 2013
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Job advert

We finally got around to prepare everything we needed to advertise the position which will be available in the MRC grant we've been awarded last year.The project will run for 30 months and we're looking for a post-doctoral candidate to work on the Rese...

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Call for participation: DMApps 2013 – an International Workshop on Data Mining Applications in Industry and Government

March 10, 2013
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Call for participation: DMApps 2013 – an International Workshop on Data Mining Applications in Industry and Government

Call for participation: DMApps 2013 – an International Workshop on Data Mining Applications in Industry and Government in conjunction with PAKDD 2013, Gold Coast, Australia, April 14, 2013 http://dmapps2013.rdatamining.com To attend the workshop, you need to register for PAKDD 2013 … Continue reading →

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Veterinary Epidemiologic Research: Linear Regression Part 2 – Checking assumptions

March 6, 2013
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Veterinary Epidemiologic Research: Linear Regression Part 2 – Checking assumptions

We continue on the linear regression chapter the book Veterinary Epidemiologic Research. Using same data as last post and running example 14.12: Now we can create some plots to assess the major assumptions of linear regression. First, let’s have a look at homoscedasticity, or constant variance of residuals. You can run a statistical test, the

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Times per second benchmark

March 5, 2013
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In GNU R the simplest way to measure execution time of a piece code is to use system.time. However, sometimes I want to find out how many times some function can be executed in one second. This is especially useful when we want to compare function...

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PCA to PLS modeling analysis strategy for WIDE DATA

March 2, 2013
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PCA to PLS modeling analysis strategy for WIDE DATA

Working with wide data is already hard enough, add to this row outliers and things can get murky fast. Here is an example of an anlysis of a wide data set, 24 rows  x 84 columns. Using imDEV, written in R, to calculate and visualize a principal components analysis (PCA) on this data set. We find that

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Normal distribution functions

February 25, 2013
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Normal distribution functions

Ah, the Central Limit Theorem.  The basis of much of statistical inference and how we get those 95% confidence intervals.  It's just so beautiful!  Lately, I have found myself looking up the normal distribution functions in R.  They...

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