In this notebook, we will apply getML to a dataset that is often used for benchmarking in the relational learning literature: The MovieLens dataset.
Author: Dr. Patrick Urbanke
The MovieLens dataset is often used in the relational learning literature has a benchmark for newly developed algorithms. Following the tradition, we benchmark getML's own algorithms on this dataset as well. The task is to predict a user's gender based on the movies they have watched.
It has been downloaded from the CTU Prague relational learning repository (Motl and Schulte, 2015).
ZEISS is working on delivering highly reliable machines and support processes. GetML allows building new predictive maintenance applications in a fraction of the time.
Automated Feature Engineering For Relational Data and Time Series