174 citations · 425 across the 33 of their papers we have counts for
6 papers · 1 filter
Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic
Lucas Baier, Niklas Kühl, Jakob Schöffer +1
As a reaction to the high infectiousness and lethality of the COVID-19 virus, countries around the world have adopted drastic policy measures to contain the pandemic. However, it r…
Switching Scheme: A Novel Approach for Handling Incremental Concept Drift in Real-World Data Sets
Lucas Baier, Vincent Kellner, Niklas Kühl +1
Machine learning models nowadays play a crucial role for many applications in business and industry. However, models only start adding value as soon as they are deployed into produ…
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting
Robin Hirt, Niklas Kühl, Yusuf Peker +1
In a variety of business situations, the introduction or improvement of machine learning approaches is impaired as these cannot draw on existing analytical models. However, in many…
Handling Concept Drifts in Regression Problems -- the Error Intersection Approach
Lucas Baier, Marcel Hofmann, Niklas Kühl +2
Machine learning models are omnipresent for predictions on big data. One challenge of deployed models is the change of the data over time, a phenomenon called concept drift. If not…
Machine Learning in Artificial Intelligence: Towards a Common Understanding
Niklas Kühl, Marc Goutier, Robin Hirt +1
The application of "machine learning" and "artificial intelligence" has become popular within the last decade. Both terms are frequently used in science and media, sometimes interc…
Needmining: Identifying micro blog data containing customer needs
Niklas Kühl, Jan Scheurenbrand, Gerhard Satzger
The design of new products and services starts with the identification of needs of potential customers or users. Many existing methods like observations, surveys, and experiments d…