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!
Mit der Data University 2019 haben wir den Start unserer ersten großen Veranstaltung gefeiert! Unsere Kollegin Anne-Marie ist teil des Marketing-Teams und hat die Veranstaltung medial begleitet. Hier sind Ihre 5 Highlights der Data University 2019.
How can you adjust your prices to meet your sales quota better? By combining sales forecasts and price elasticity estimations, you can make recommendations to increase the profit. In this blog post, Marlon will show you how to combine both methods.
As a REST API, Livy provides Spark interaction without any need of a Spark configuration on your client. Once being able to communicate with the API Spark code can be submitted from everywhere.
Besides working hard to provide our clients with cutting-edge Machine Learning solutions, we are also big fans of all things culinary here at STATWORX. But can we apply some of those algorithms to make us better cooks? This blog article explores the unlikely union of Data Science and baking!
Last Sunday, part of our STATWORX crew went on a day trip to the picturesque Rheingau, the famous wine region known for its Riesling. The trip was planned around the three tourist pillars of the region: wine, castles & hiking.
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.
Cross-validation is a widely used technique to assess the generalization performance of a machine learning model. In this blog post I will introduce the basics of cross-validation, provide guidelines to tweak its parameters, and illustrate how to build it from scratch in an efficient way.
This blog post looks at how we can improve predictive accuracy by combining forecasts from different models.