Search Results for author:
Found 10 papers, 4 papers with code
Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection
Among these methods, Kernel SHAP is widely used due to its model-agnostic nature and its well-founded theoretical framework.
LCE: An Augmented Combination of Bagging and Boosting in Python
lcensemble is a high-performing, scalable and user-friendly Python package for the general tasks of classification and regression.
Generating robust counterfactual explanations
Counterfactual explanations have become a mainstay of the XAI field.
Persistence-Based Discretization for Learning Discrete Event Systems from Time Series
After the study of the persistence score, we point out that it tends to favor excessive cases making it miss interesting persisting symbols.
VCNet: A self-explaining model for realistic counterfactual generation
Our contribution is the generation of counterfactuals that are close to the distribution of the predicted class.
Discovering Useful Compact Sets of Sequential Rules in a Long Sequence
We are interested in understanding the underlying generation process for long sequences of symbolic events.
HiPaR: Hierarchical Pattern-aided Regression
We introduce HiPaR, a novel pattern-aided regression method for tabular data containing both categorical and numerical attributes.
XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification
Then, we illustrate how XCM reconciles performance and explainability on a synthetic dataset and show that XCM enables a more precise identification of the regions of the input data that are important for predictions compared to the current deep learning MTS classifier also providing faithful explainability.
XEM: An Explainable-by-Design Ensemble Method for Multivariate Time Series Classification
We present XEM, an eXplainable-by-design Ensemble method for Multivariate time series classification.
Statistically Significant Discriminative Patterns Searching
Discriminative pattern mining is an essential task of data mining.
