Benchmarking your code is one thing – another thing is to keep and use the gained knowledge for future projects. In this blog, Jakob presents his collection of benchmarks and creates an easy to use a setup for new ones.
Training random forests on time series is one thing, but tuning them? It’s not like you can just apply cross validation and be done with it. Or can you? This post forms part two our mini-series “Time Series Forecasting with Random Forest”. Find out how you can tune the hyperparameters of the random forest algorithm when dealing with time series data. The answers might surprise you!
rBokeh is an interactive plotting library. Since it functions lack some arguments compared to its Python counterpart, plots are sometimes difficult to customize. I will show how to overcome those issues and drill out the plot objects.
Want to obtain a specific dataset from a website which does not have an API? In this post, I explain how to do this by scraping data using Python, how you determine whether it is allowed to scrape a specific page and more.
In this blog article, you will learn you how to set up a dashboard with the flexdashboard package, how to integrate interactive widgets and how to deploy the app on shinyapps.io.
Never heard of non-standard evaluation? Then our colleague Markus has the perfect answer for you: Bang Bang! In this blog post, Markus introduces meta-programming when using dplyr.
It is June and nearly half of the year is over, marking the middle between Christmas 2018 and 2019. Last year in autumn, I’ve published a blog post about predicting Wham’s „Last Christmas“ search volume using Google Trends data with different types of neural network architectures. Of course, now I want to know how good the predictions were, compared to …
In my last blog post, I have elaborated on the Bagging algorithm and showed its prediction performance via simulation. Here, I want to go into the details on how to simulate the bias and variance of a nonparametric regression fitting method using R. These kinds of questions arise here at STATWORX when developing, for example, new machine learning algorithms or …
Do you want to optimise your code but don’t know where to start? In this post I guide you through my thought process when I optimised my code.