3222 search results for "MAP"

Ensemble Methods Part 3: Revolution Analytics Big Data Random Forest Function

May 20, 2014
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Ensemble Methods Part 3: Revolution Analytics Big Data Random Forest Function

by Mike Bowles In two previous posts, A Thumbnail History of Ensemble Methods and Ensemble Packages in R, Mike Bowles — a machine learning expert and serial entrepreneur — laid out a brief history of ensemble methods and described a few of the many implementations in R. In this post Mike takes a detailed look at the Random Forests...

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taxize v0.3.0 update – a new data source, taxonomy in writing, and uBio examples

May 20, 2014
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We just released v0.3 of taxize. For details on the update, see the release notes. Some new features New function iplant_resolve() to do name resolution using the iPlant name resolution service. Note, this is different from http://taxosaurus.org/ that is wrapped in the tnrs() function. New function ipni_search() to search for names in the International Plant Names Index (IPNI). See...

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Next Kölner R User Meeting: Friday, 23 May 2014

May 20, 2014
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Next Kölner R User Meeting: Friday, 23 May 2014

The next Cologne R user group meeting is scheduled for this Friday, 23 May 2014. To celebrate our 10th meeting we welcome: Andrie de Vries (Revolution Analytics and Co-author of R for Dummies): Taking R to the Enterprise Markus Gesmann: googleVis overview and recent developments Followed by drinks and schnitzel at the Lux.Further details available on our...

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Deploying Shiny Server on Amazon: Some Troubleshoots and Solutions

May 18, 2014
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Deploying Shiny Server on Amazon: Some Troubleshoots and Solutions

I really enjoyed Treb Allen‘s tutorial on deploying a Shiny server on an Amazon Cloud Instance. I used this approach for my shiny app that is a map highlighting the economic impact of the recent shale oil and gas boom on the places where the actual extraction happens. The easiest way to proceed is to

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R is short for SSIS

May 18, 2014
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R is Short for SSIS Data scientists often identify a need to join data from different, unlinked servers. One standard tool for accomplishing this is an SSIS package to consolidate the data onto one of the servers. For the analyst who wants to...

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Vectorizing IPv4 Address Conversions – Part 2

May 17, 2014
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Vectorizing IPv4 Address Conversions – Part 2

The previous post looked at using the Vectorize() function to, well, vectorize, our Rcpp IPv4 functions. While this is a completely acceptable practice, we can perform the vectorization 100% in Rcpp/C++. We’ve included both the original Rcpp IPv4 functions and the new Rcpp-vectorized functions together to show the minimal differences between them: #include <Rcpp.h> #include <boost/asio/ip/address_v4.hpp> using namespace Rcpp; using namespace boost::asio::ip; // Rcpp/C++ vectorized routines // ] NumericVector rcpp_rinet_pton (CharacterVector...

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RGolf

May 16, 2014
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Its time for some fun today - because its Friday as David Smith says :).There are many code golf sites, even some support R. However, most of them are algorithm oriented. A true RGolf competition should involve transforming a source data frame to some ...

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R has some sharp corners

May 15, 2014
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R has some sharp corners

R is definitely our first choice go-to analysis system. In our opinion you really shouldn’t use something else until you have an articulated reason (be it a need for larger data scale, different programming language, better data source integration, or something else). The advantages of R are numerous: Single integrated work environment. Powerful unified scripting/programming Related posts:

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The apply command 101

May 15, 2014
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The apply command 101

The goal of this blog entry is to introduce basic and essential information about the apply function. Even established R users get confused when considering this family of functions especially when observing how many of the them there are: apply, tapply, lapply, sapply, rapply, eapply, mapply. When I was new to R I was rarely

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qqman: an R package for creating Q-Q and manhattan plots from GWAS results

May 15, 2014
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qqman: an R package for creating Q-Q and manhattan plots from GWAS results

Three years ago I wrote a blog post on how to create manhattan plots in R. After hundreds of comments pointing out bugs and other issues, I've finally cleaned up this code and turned it into an R package.The qqman R package is on CRAN: http://cran.r-project.org/web/packages/qqman/The source code is on GitHub: https://github.com/stephenturner/qqmanIf you'd like to cite the...

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