193 search results for "iris"

Principal Component Analysis on Imaging

December 25, 2014
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Principal Component Analysis on Imaging

Ever wonder what's the mathematics behind face recognition on most gadgets like digital camera and smartphones? Well for most part it has something to do with statistics. One statistical tool that is capable of doing such feature is the Principal Component Analysis (PCA). In this post, however, we will not do (sorry to disappoint you) face recognition as...

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Hassle-free data from HTML tables with the htmltable package

December 15, 2014
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HTML tables are a standard way to display tabular information online. Getting HTML table data into R is fairly straightforward with the readHTMLTable() function of the XML package. But tables on the web are primarily designed for displaying and consuming data, not for analytical purposes. Peculiar design choices for HTML tables are therefore frequently made which tend to produce...

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The ensurer package (validation inside pipes)

November 19, 2014
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The ensurer package (validation inside pipes)

Guest post by Stefan Holst Milton Bache on the ensurer package. If you use R in a production environment, you have most likely experienced that some circumstances change in ways that will make your R scripts run into trouble. Many things can go wrong; package updates, external data sources, daylight savings time, etc. There is a general

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High performance JSON streaming in R: Part 1

November 5, 2014
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High performance JSON streaming in R: Part 1

The jsonlite stream_in and stream_out functions implement line-by-line processing of JSON data over a connection, such as a socket, url, file or pipe. Thereby we can construct a data processing pipeline that can handle large (or unlimited) amounts of data with limited memory. This post will walk through some examples...

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A Note on Tweedie

October 9, 2014
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A Note on Tweedie

by Joseph Rickert In a recent post I talked about the information that can be developed by fitting a Tweedie GLM to a 143 million record version of the airlines data set. Since I started working with them about a year or so ago, I now see Tweedie models everywhere. Basically, any time I come across a histogram that...

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Deep Down Below – Using in-database analytics from within Tableau (with MADlib)

September 28, 2014
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Deep Down Below – Using in-database analytics from within Tableau (with MADlib)

Introduction Using Tableau for visualizing all kinds of data is quite a joy, but it’s not that strong on build-in analytics or predictive features. Tableaus integration of R was a huge step in the right direction (and I love it very much - see here, here and here) but still has some limitations (e.g. no RAWSQL...

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How to publish R and ggplot2 to the web

September 23, 2014
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How to publish R and ggplot2 to the web

by Matt Sundquist, Plotly Co-founder It's delightfully smooth to publish R code, plots, and presentations to the web. For example: Shiny makes interactive apps from R. Pretty R highlights R code for HTML. Slidify makes slides from R Markdown. Knitr and RPubs let you publish R Markdown docs. GitHub and devtools let you quickly release packages and collaborate. Now,...

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Lazy load with archivist

September 22, 2014
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Lazy load with archivist

Version 1.1 of the archivist package reached CRAN few days ago. This package supports operations on disk based repository of R objects. It makes the storing, restoring and searching for an R objects easy (searching with the use of meta information). Want to share your object with article reviewers or collaborators? This package should help.

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Webinar September 25: Data Science with R

September 19, 2014
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A quick heads up that if you'd like to get a great introduction to doing data science with the R language, Joe Rickert will be giving a free webinar next Thursday, September 25: Data Science with R. Regular readers of the blog will be familiar with Joe's posts on this topic. A few recent examples include posts on comparing...

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Pander tables inside of knitr

September 18, 2014
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Pander tables inside of knitr

Hadley Wickham opened my eyes that calling pander to generate nifty markdown tables inside of knitr requires a special chunk option, which bothersome extra step might be saved by updating pander a bit. So it's done.In a nutshell, whenever you...

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