R Weekly

February 20, 2017
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R Weekly

During my Monday morning ritual of avoiding work,  I found this publication that is written in R, for people who use R – R Weekly.  The authors do a pretty awesome job of aggregating useful, entertaining, and informative content about what’s happening surrounding our favorite programming language.  Check it out, give the authors some love on GitHub, and leave … Continue...

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rxNeuralNet vs. xgBoost vs. H2O

February 20, 2017
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rxNeuralNet vs. xgBoost vs. H2O

Recently, I did a session at local user group in Ljubljana, Slovenija, where I introduced the new algorithms that are available with MicrosoftML package for Microsoft R Server 9.0.3....

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strcode – structure your code better

strcode – structure your code better

I am pleased to announce my package strcode, a package that should make structuring code easier. You can install it from GitHub, a CRAN submission is planned at a...

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Data Science for Doctors – Part 4 : Inferential Statistics (1/5)

February 20, 2017
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Data Science for Doctors – Part 4 : Inferential Statistics (1/5)

Data science enhances people’s decision making. Doctors and researchers are making critical decisions every day. Therefore, it is absolutely necessary for those people to have some basic knowledge of...

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PCA – hierarchical tree – partition: Why do we need to choose for visualizing data?

February 20, 2017
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PCA – hierarchical tree – partition: Why do we need to choose for visualizing data?

Principal component methods such as PCA (principal component analysis) or MCA (multiple correspondence analysis) can be used as a pre-processing step before clustering. But principal component methods give also a framework...

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More tidyverse: using dplyr functions

February 20, 2017
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This week, we return to our “Getting Started With R” series. Today we are going to look at some tools from the “dplyr” package. Hadley Wickham, the creator of dplyr,...

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Is my time series additive or multiplicative?

February 20, 2017
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Is my time series additive or multiplicative?

Time series data is an important area of analysis, especially if you do a lot of web analytics. To be able to analyse time series effectively, it helps to...

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future: Reproducible RNGs, future_lapply() and more

February 19, 2017
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future: Reproducible RNGs, future_lapply() and more

future 1.3.0 is available on CRAN. With futures, it is easy to write R code once, which the user can choose to evaluate in parallel using whatever resources...

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SatRday and visual inference of vine copulas

February 19, 2017
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SatRday and visual inference of vine copulas

SatRday From the 16th to the 18th of February, satRday was held in the City of Cape Town in South Africa. The programme kicked off with two days of workshops...

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Building Shiny App exercises part 7

February 19, 2017
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Building Shiny App exercises part 7

Connect widgets & plots In the seventh part of our journey we are ready to connect more of the widgets we created before with our k-means plot in order...

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Factoextra R Package: Easy Multivariate Data Analyses and Elegant Visualization

February 19, 2017
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Factoextra R Package: Easy Multivariate Data Analyses and Elegant Visualization

factoextra is an R package making easy to extract and visualize the output...

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padr::pad does now do group padding

February 18, 2017
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A few weeks ago padr was introduced on CRAN, allowing you to quickly get datetime data ready for analysis. If you have missed this, see the introduction blog or...

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Predicting food preferences with sparklyr (machine learning)

February 18, 2017
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Predicting food preferences with sparklyr (machine learning)

This week I want to show how to run machine learning applications on a Spark cluster. I am using the sparklyr package, which provides a handy interface to access...

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Bar bar plots but not Babar plots

February 18, 2017
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Bar bar plots but not Babar plots

You might have heard of the “bar bar plots” movement whose goal is to prevent using (let’s use ggplot2 language shall we) geom_bar when you could have used e.g....

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Using Rcpp with C++11, C++14 and C++17

February 18, 2017
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Using Rcpp with C++11, C++14 and C++17

Background When we started the Rcpp Gallery in late 2012, a few of us spent the next four weeks diligently writing articles ensuring that at least one new article would be...

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Analytical and Numerical Solutions to Linear Regression Problems

February 18, 2017
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Analytical and Numerical Solutions to Linear Regression Problems

This exercise focuses on linear regression with both analytical (normal equation) and numerical (gradient descent) methods. We will start with linear regression with one variable. From this part of...

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Putting It All Together

February 18, 2017
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Putting It All Together

The kind folks over at @RStudio gave a nod to my recently CRAN-released epidata package in their January data package roundup and I thought it might be useful to...

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cricketr and yorkr books – Paperback now in Amazon

February 18, 2017
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cricketr and yorkr books – Paperback now in Amazon

My books – Cricket Analytics with cricketr – Beaten by sheer pace!: Cricket analytics with yorkr are now available on Amazon in both Paperback and Kindle versions The cricketr...

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Accessing MSSQL Server with R (RSQLServer with dplyr)

February 18, 2017
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Accessing MSSQL Server with R (RSQLServer with dplyr)

Recently I have been starting to use dplyr for handling my data in R. It makes everything a lot smoother! My previous workflow – running an SQL query, storing...

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RPushbullet 0.3.1

February 17, 2017
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RPushbullet 0.3.1

A new release 0.3.1 of the RPushbullet package, following the recent 0.3.0 release is now on CRAN. RPushbullet is interfacing the neat Pushbullet service for inter-device messaging, communication,...

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Using Armadillo with SuperLU

February 17, 2017
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Using Armadillo with SuperLU

Armadillo is very versatile C++ library for linear algebra, brough to R via the RcppArmadillo package. It has proven to be very useful and popular, and is (as of February...

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A plot against the CatterPlots complot

February 17, 2017
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A plot against the CatterPlots complot

In these terrible times, we R people have more important subjects to debate/care about than ggplot2 vs. base R graphics (isn’t even worth discussing anyway, ggplot2 is clearly the...

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Optimization and Operations Research in R

February 17, 2017
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Authors: Stefan Feuerriegel and Joscha Märkle-Huß R is widely taught in business courses and, hence, known by most data scientists with business background. However, when it comes to optimization...

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Catterplots: Plots with cats

February 17, 2017
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Catterplots: Plots with cats

As a devotee of Tufte, I'm generally against chartjunk. Graphical elements that obscure interpretation of the data occasionally have a useful role to play, but more often than not...

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January New Data Packages

February 17, 2017
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January New Data Packages

by Joseph Rickert As forecast, the number of R packages hosted on CRAN exceeded 10,000 in January. Dirk Eddelbuettel, who tracks what’s happening on CRAN with his CRANberries site,...

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Naive Bayes Classification in R (Part 2)

February 17, 2017
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Naive Bayes Classification in R (Part 2)

Following on from Part 1 of this two-part post, I would now like to explain how the Naive Bayes classifier works before applying it to a classification problem involving...

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Naive Bayes Classification in R (Part 1)

February 17, 2017
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Naive Bayes Classification in R (Part 1)

Introduction A very useful machine learning method which, for its simplicity, is incredibly successful in many real world applications is the Naive Bayes classifier. I am currently taking a...

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How to perform PCA with R?

February 17, 2017
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How to perform PCA with R?

This post shows how to perform PCA with R and the package FactoMineR. If you want to learn more on methods such as PCA, you can enroll in this...

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Moving largish data from R to H2O – spam detection with Enron emails

February 17, 2017
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Moving largish data from R to H2O – spam detection with Enron emails

Moving around sparse matrices of text data - the limitations of as.h2o This post is the resolution of a challenge I first wrote about in late 2016, moving large sparse...

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