160 citations · 356 across the 38 of their papers we have counts for
45 papers
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…
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…
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…
Online Learning of Decision Trees with Thompson Sampling
Ayman Chaouki, Jesse Read, Albert Bifet
Decision Trees are prominent prediction models for interpretable Machine Learning. They have been thoroughly researched, mostly in the batch setting with a fixed labelled dataset,…