Tag: Hadoop

Feed: R-bloggers. Author: Digital Age Economist on Digital Age Economist. Join Andrew Collier and Hanjo Odendaal for a workshop on using R for Web Scraping. Who should attend? This workshop is aimed at beginner and intermediate R users who want to learn more about using R for data acquisition and management, with a specific focus on web scraping. What will you learn? You will learn: data manipulation with dplyr, tidyr and purrr; tools for accessing the DOM; scraping static sites with rvest; scraping dynamic sites with RSelenium; and setting up an automated scraper in the cloud. See programme below for ... Read More

Feed: R-bloggers. Author: Appsilon Data Science Blog. I spent 3 amazing days at eRum conference in Budapest. The conference was a blast and organizers (BIG thanks to them again) did wonderful job compiling such a high-level event. My favourite talks from the conference Better than Deep Learning – Gradient Boosting Machines (GBM) in R – Szilard Pafka Szilard made a thorough overview of currently available ML algorithms. Showed that ML algorithm works better on tabular data than Deep Learning. Gave his advice on which packages to choose depending on your goals like maximizing speed on GPU/CPU or going to production ... Read More

Feed: R-bloggers. Author: Ilya Kashnitsky. Tiny things can separate life into “before” and “after”. Here is one. For almost a year I’ve been daily sending mental “thank you” to Ugo (@ugobas) who showed me how to re-organize panes in RStudio. Since then I’ve been spreading this tiny improvement so many times that I thought the tiny advise deserved a separate tiny post. Please note, below is an opinionated view of a comfortable UI improvement; feel free to ignore it if you don’t like. This advise is highly subjective, though, I really believe it is useful. I find the default 4-pane ... Read More

Feed: R-bloggers. Author: Aman Tsegai. We’re finally here. Datazar Paper is the most exciting tool we’ve created to date. Up until now, I’d like to believe we’ve only made par with the status quo in terms of the tools we have developed for our beloved community of industry researchers, hackers and academics. We have a vision at Datazar where researchers would eventually be able to create and consume research in one, continious cycle. We introduced tools like Replication (ability to replicate a research project simply by clicking a button), Discussions (real time chat where you can exchange code snippets etc…) ... Read More

Feed: R-bloggers. Author: Biswarup Ghosh. In the exercises below, we will work with FFTree pacakge which lets us use fast and frugal decision tree to model the data Please install the package and load the library before startingAnswers to these exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page. Exercise 1 FFTree package comes with heart.train,heart.test data .Check the heart.train data and see the diagnosis column .This is our response variable .Create a FFTree model using heart.test,heart.train and ... Read More

Feed: R-bloggers. Author: Ewen Harrison. Thank you for the many requests to provide some extra info on how best to get finalfit results out of RStudio, and particularly into Microsoft Word. Here is how. Make sure you are on the most up-to-date version of finalfit. devtools::install_github("ewenharrison/finalfit") What follows is for demonstration purposes and is not meant to illustrate model building. Does a tumour characteristic (differentiation) predict 5-year survival? Demographics table First explore variable of interest (exposure) by making it the dependent. library(finalfit) library(dplyr) dependent = "differ.factor" # Specify explanatory variables of interest explanatory = c("age", "sex.factor", "extent.factor", "obstruct.factor", "nodes") Note ... Read More

Feed: R-bloggers. Author: scottmutchler. First, let me say I would love to have an “easy button” for predictive analytics. Unfortunately, predictive analytics is hard work that requires deep subject matter expertise in both the business problem and data science.  I’m not trying to be provocative with this post.  I just want to share my viewpoint over many year of experience. ————- There are a couple of myths that I see more an more these days.  Like many myths they seem plausible on the surface but experienced data scientist know that the reality is more nuanced (and sadly requires more work) ... Read More

Feed: R-bloggers. Author: Marcin Kosiński. We are pleased to announance upcoming Why R? 2018 conference that is going to happen in central-eastern Europe (Poland, Wroclaw) this July (2-5th). It is the last week for the call for papers! Submit your talk here. More about the conference one can find on the conference website whyr2018.pl and in the previous blog post we’ve prepared Why R? 2018 Conference – Registration and Call for Papers Opened. The general overview We are organizing pre-meetings in many European cities to cultivate the R experience of knowledge sharing. You are more than welcome to visit upcoming ... Read More

Feed: R-bloggers. Author: . How Has Taylor Swift’s Word Choice Changed Over Time?Sunday night was a big night for Taylor Swift – not only was she nominated for multiple Billboard Music Awards; she took home Top Female Artist and Top Selling Album. So I thought it was a good time for some more Taylor Swift-themed statistical analysis. When I started this blog back in 2011, my goal was to write deep thoughts on trivial topics – specifically, to overthink and overanalyze pop culture and related topics that appear fluffy until you really dig into them. Recently, I’ve been blogging more ... Read More

Feed: R-bloggers. Author: Dominique Makowski. Yes, the correlation function from the psycho package. devtools::install_github("neuropsychology/psycho.R") # Install the newest version library(psycho) library(tidyverse) cor psycho::affective %>% correlation() This function automatically select numeric variables and run a correlation analysis. It returns a psychobject. We can then extract a formatted table that can be saved and pasted into reports and manuscripts by using the summary function. summary(cor) # write.csv(summary(cor), "myformattedcortable.csv")   Age Life_Satisfaction Concealing Adjusting Age         Life_Satisfaction 0.03       Concealing -0.05 -0.06     Adjusting 0.03 0.36*** 0.22***   Tolerating 0.03 0.15*** 0.07 0.29*** It integrates a plot ... Read More