R-bloggers

You might be eager to deploy your Shiny app to a remote server. But the simplest way to run a Shiny app is to run it locally. You only need the shiny R package installed, and you can run the app in your browser.

Images are an increasingly used data source in the social sciences. One application is to extract features from human faces using machine learning algorithms. This blog post provides a guide on using APIs for this task, specifically how to ...

This is the latest in my series of screencasts demonstrating how to use the tidymodels packages, from just starting out to tuning more complex models with many hyperparameters. Today’s screencast walks through how to build features for modeling from ...

In a “Feature” article of 21 January 2021, Nature goes over a poll on “software tools that have had a big impact on the world of science”. Among those, the Fortran compiler (1957), which is one of the first symbolic languages, developed by IBM. This is the first computer language I learned (in 1982) ...

Hello, welcome to part 2 of the series building a model to predict fantasy premier league points. If you missed the first part which i did some initial EDA go check it out here Building a Model in R to Predict FPL Points As I identified before the first part of ...

22.04.2021 I released a new version of Bio7. Bio7 3.3 includes a plethora of new features, improvements and bugfixes. For those who don’t know Bio7. The application Bio7 is an integrated development environment for ecological modeling, scientific image analysis and statistical analysis. It also contains a feature complete development environment for ...

I recently came across a term synthetic data. I start wondering what does it mean? I found that it is […] The post Can we rely on synthetic data to overcome data governance issue in healthcare? appeared first on NHS-R Community.

Social Network Analysis in R, Social Network Analysis (SNA) is the process of exploring the social structure by using graph theory. It is mainly... The post Social Network Analysis in R appeared first on finnstats.

The NHS-R community commissioned a package at the start of the year to address the need to pull lookups real time from the NHS Data Dictionary website. I thought this would be a good package, but what I have included, in addition, is the ability to scrape tables and text ...

Introduction The Hosmer-Lemeshow test (HL test) is a goodness of fit test for binary classification models which tells how well data fits a given model. Specifically, the HL test calculates if the observed event rates match the expected event rates in population subgroups and could be used as a supporting ...

By my count, two hundred twenty-one new packages stuck to CRAN in March 2021.1 Here are my “Top 40” selections in twelve categories: Computational Methods, Data, Engineering, Genomics, Machine Learning, Medicine, Music, Networks, Science, Statistics, Utility, and Visualization. Two of these categories Engineering and Music have only one entry each. However, I ...

A question that came out on X validated a few days ago is how to efficiently simulate from a distribution with density x²φ(x). (Obviously properly normalised since the second moment of the standard Normal  distribution is one.) The first solution that came out (by Jarle Tufto) exploits the fact ...

Background In a previous post I was toying with better ways to integrate monoclonal proteins by deconvolution of monoclonal peaks. Turns out this is a hard problem. In any case, Deep Learning Neural Networks have become so mature that I wanted to see how easy it is to identify the ...

Setup Loading the R libraries and data set. # Loading libraries library(tidyverse) library(tidytext) library(tidytuesdayR) library(forcats) # Loading data set tt

Quantile Regression Example Quantile Regression Forest Review Performance Coverage Interval Width Closing Notes Appendix Residual Plots Other Charts In this post I will build prediction intervals using quantile regression, more specifically, quantile regression forests. This is my third post on prediction intervals. Prior posts: Understanding Prediction Intervals (Part 1) Simulating Prediction ...

Must-Have Skills for Data Science Everybody and their mother wants to learn data science. And there’s no reason not to – the job you do is interesting 95% of the time, the salaries are excellent, and most likely you can get the job done from the comfort of your bed.  You ...

New Course Available Now: Machine Learning with Tidymodels The ever increasing application of machine learning models in industry and academia requires tools which are easy to use and ensure a reliable model fitting process. The R package universe cov...

Cluster Analysis in R, when we do data analytics, there are two kinds of approaches one is supervised and another is unsupervised. Clustering is... The post Cluster Analysis in R appeared first on finnstats.