Feb 11, 2019 · Abstract:We study the problem of interpreting trained classification models in the setting of linguistic data sets. Leveraging a parse tree, ...
The LS-Tree value can be interpreted as supplying the coefficients of the best linear model used to approximate the target model locally for each instance.
Jul 4, 2020 · We study the problem of interpreting trained classification models in the setting of linguistic data sets. Leveraging a parse tree, we propose ...
A linear approximation at nodes of the tree. An axiomatic framework based on Banzhaf value. Capture the influence of instance i: : Fit a linear model without ...
L-shapley and c-shapley: Efficient model interpretation for structured data. J ... Ls-tree: Model interpretation when the data are linguistic. J Chen, M Jordan.
LS-Tree: Model Interpretation When the Data Are Linguistic. J. Chen, and M. Jordan. CoRR, (2019 ). Links and resources. BibTeX key: journals/corr/abs-1902 ...
We study the problem of interpreting trained classification models in the setting of linguistic data sets. Leveraging a parse tree, we.
Chen, J. and Jordan, M. 2020. LS-Tree: Model Interpretation When the Data Are Linguistic. Proceedings of the AAAI Conference on Artificial Intelligence.
Mar 21, 2024 · LS-Tree: Model interpretation when the data are linguistic. ... L-Shapley and C-Shapley: Efficient model interpretation for structured data.
