7 papers · 1 filter
Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information
Ben Halstead, Yun Sing Koh, Patricia Riddle +3
Streaming sources of data are becoming more common as the ability to collect data in real-time grows. A major concern in dealing with data streams is concept drift, a change in the…
Simulation-Driven Railway Delay Prediction: An Imitation Learning Approach
Clément Elliker, Jesse Read, Sonia Vanier +1
Reliable prediction of train delays is essential for enhancing the robustness and efficiency of railway transportation systems. In this work, we reframe delay forecasting as a stoc…
Binary Split Categorical feature with Mean Absolute Error Criteria in CART
Peng Yu, Yike Chen, Chao Xu +2
In the context of the Classification and Regression Trees (CART) algorithm, the efficient splitting of categorical features using standard criteria like GINI and Entropy is well-es…
BELLA: Black box model Explanations by Local Linear Approximations
Nedeljko Radulovic, Albert Bifet, Fabian Suchanek
Understanding the decision-making process of black-box models has become not just a legal requirement, but also an additional way to assess their performance. However, the state of…
Branches: Efficiently Seeking Optimal Sparse Decision Trees with AO*
Ayman Chaouki, Jesse Read, Albert Bifet
Decision Tree (DT) Learning is a fundamental problem in Interpretable Machine Learning, yet it poses a formidable optimisation challenge. Practical algorithms have recently emerged…
A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streams
Ben Halstead, Yun Sing Koh, Patricia Riddle +2
The distribution of streaming data often changes over time as conditions change, a phenomenon known as concept drift. Only a subset of previous experience, collected in similar con…