1276 search results for "LateX"

A quick introduction to machine learning in R with caret

April 6, 2016
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A quick introduction to machine learning in R with caret

If you’ve been using R for a while, and you’ve been working with basic data visualization and data exploration techniques, the next logical step is to start learning some machine learning. To help you begin learning about machine learning in R, I’m going to introduce you to an R package: the caret package. We’ll build The post

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Election analysis contest entry part 2 – building the nzelect R package

April 3, 2016
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Election analysis contest entry part 2 – building the nzelect R package

Motivation This post is the second in a series that make up my entry in Ari Lamstein’s R Election Analysis Contest, Yesterday I introduced the nzelect R package from a user perspective. Today I’m writing about how the build of that package works. This might be of interest to someone planning on doing something...

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Jupyter Notebooks with R in Azure Machine Learning Studio

March 30, 2016
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Jupyter Notebooks with R in Azure Machine Learning Studio

by Andrie de Vries Earlier today Microsoft announced that Jupyter Notebooks are now available with the R Kernel as a service in Azure Machine Learning (ML) Studio. I wrote about Jupyter Notebooks in September 2015 (Using R with Jupyter Notebooks), where I noted some of the great benefits of using notebooks: Jupyter is an easy to use and convenient...

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Dealing with non-proportional hazards in R

March 29, 2016
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Dealing with non-proportional hazards in R

As things change over time so should our statistical models. The image is CC by Prad Prathivi Since I'm frequently working with large datasets and survival data I often find that the...

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R for Publication by Page Piccinini

March 23, 2016
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R for Publication by Page Piccinini

The goal of this course is to give you the skills to do the statistics that are in current published papers, and make pretty figures to show off your results. While we will go over the mathematical concepts behind the statistics, this is NOT meant to be a classical statistics class. We will focus more Lesson 0: Introduction...

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R Markdown Custom Formats

March 21, 2016
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R Markdown Custom Formats

The R Markdown package ships with a raft of output formats including HTML, PDF, MS Word, R package vignettes, as well as Beamer and HTML5 presentations. This isn’t the entire universe of available formats though (far from it!). R Markdown formats are fully extensible and as a result there are several R packages that provide additional formats.

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Stemming and Spell Checking in R

March 20, 2016
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Stemming and Spell Checking in R

Last week we introduced the new hunspell R package. This week a new version was released which adds support for additional languages and text analysis features. Additional languages By default hunspell uses the US English dictionary en_US but the new version allows for checking and analyzing in other languages as well. The ?hunspell...

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Hunspell: Spell Checker and Text Parser for R

March 13, 2016
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Hunspell: Spell Checker and Text Parser for R

Hunspell is the spell checker library used in LibreOffice, OpenOffice, Mozilla Firefox, Google Chrome, Mac OS X, InDesign, and a few more. Base R has some spell checking functionality via the aspell function which wraps the aspell or hunspell command line program on supported systems. The new hunspell R package on...

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R 3.2.4 is released

March 11, 2016
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R 3.2.4 is released

R 3.2.4 (codename “Very Secure Dishes”) was released today. You can get the latest binaries version from here. (or the .tar.gz source code from here). The full list of new features and bug fixes is provided below. Upgrading to R 3.2.4 on Windows If you are using Windows you can easily upgrade to the latest version of R using the installr … Continue reading...

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preserving frequencies without resampling

March 8, 2016
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preserving frequencies without resampling

An interesting question came up on X validated a few days ago: given a probability vector p=(p¹,…,p⁷), is there a way to pick 5 values in {1,…,7} without replacement and still preserve the probability repartition in the resulting sample? In other words, is there a sampling without replacement strategy that leads to for i=1,…,7..? Unless

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