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Strong optimal classification trees
Decision trees are among the most popular machine learning models and are used routinely
in applications ranging from revenue management and medicine to bioinformatics. In this …
in applications ranging from revenue management and medicine to bioinformatics. In this …
Learning optimal fair decision trees: Trade-offs between interpretability, fairness, and accuracy
The increasing use of machine learning in high-stakes domains–where people's livelihoods
are impacted–creates an urgent need for interpretable, fair, and highly accurate algorithms …
are impacted–creates an urgent need for interpretable, fair, and highly accurate algorithms …
Optimal or Greedy Decision Trees? Revisiting their Objectives, Tuning, and Performance
Decision trees are traditionally trained using greedy heuristics that locally optimize an
impurity or information metric. Recently there has been a surge of interest in optimal …
impurity or information metric. Recently there has been a surge of interest in optimal …
Shattering inequalities for learning optimal decision trees
Recently, mixed-integer programming (MIP) techniques have been applied to learn optimal
decision trees. Empirical research has shown that optimal trees typically have better out-of …
decision trees. Empirical research has shown that optimal trees typically have better out-of …
Improving stability in decision tree models
Owing to their inherently interpretable structure, decision trees are commonly used in
applications where interpretability is essential. Recent work has focused on improving …
applications where interpretability is essential. Recent work has focused on improving …
Adversarially robust decision tree relabeling
Decision trees are popular models for their interpretation properties and their success in
ensemble models for structured data. However, common decision tree learning algorithms …
ensemble models for structured data. However, common decision tree learning algorithms …
Interpretable data‐driven contingency classification for real‐time corrective security‐constrained economic dispatch
Y Yu, Y Gao, Y Li, Y Yan - IET Renewable Power Generation, 2024 - Wiley Online Library
High penetrations of renewable energy are crucial for low‐carbon power systems. However,
the higher volatility of renewable power generation pushes real‐time operations closer to …
the higher volatility of renewable power generation pushes real‐time operations closer to …
Optimal multivariate decision trees
Recently, mixed-integer programming (MIP) techniques have been applied to learn optimal
decision trees. Empirical research has shown that optimal trees typically have better out-of …
decision trees. Empirical research has shown that optimal trees typically have better out-of …
Strong optimal classification trees
Decision trees are among the most popular machine learning models and are used routinely
in applications ranging from revenue management and medicine to bioinformatics. In this …
in applications ranging from revenue management and medicine to bioinformatics. In this …
[HTML][HTML] Optimal shapelets tree for time series interpretable classification
Time series shapelets are a state-of-the-art data mining technique that is applied to time
series supervised classification tasks. Shapelets are defined as subsequences that retain …
series supervised classification tasks. Shapelets are defined as subsequences that retain …