Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Takagi, Takuya"'
This paper proposes a new algorithm for learning accurate tree-based models while ensuring the existence of recourse actions. Algorithmic Recourse (AR) aims to provide a recourse action for altering the undesired prediction result given by a model. T
Externí odkaz:
http://arxiv.org/abs/2406.01098
Machine learning models need to be continually updated or corrected to ensure that the prediction accuracy remains consistently high. In this study, we consider scenarios where developers should be careful to change the prediction results by the mode
Externí odkaz:
http://arxiv.org/abs/2310.06446
This paper proposes a new framework of algorithmic recourse (AR) that works even in the presence of missing values. AR aims to provide a recourse action for altering the undesired prediction result given by a classifier. Existing AR methods assume th
Externí odkaz:
http://arxiv.org/abs/2304.14606
The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a text string $T$ of length $n$ has $O(n)$ nodes and edges, and the string label of each edge is encoded by a pair of positions in $T$. Thus,
Externí odkaz:
http://arxiv.org/abs/2301.04295
Autor:
Wang, Zijie J., Zhong, Chudi, Xin, Rui, Takagi, Takuya, Chen, Zhi, Chau, Duen Horng, Rudin, Cynthia, Seltzer, Margo
Given thousands of equally accurate machine learning (ML) models, how can users choose among them? A recent ML technique enables domain experts and data scientists to generate a complete Rashomon set for sparse decision trees--a huge set of almost-op
Externí odkaz:
http://arxiv.org/abs/2209.09227
In any given machine learning problem, there may be many models that could explain the data almost equally well. However, most learning algorithms return only one of these models, leaving practitioners with no practical way to explore alternative mod
Externí odkaz:
http://arxiv.org/abs/2209.08040
Publikováno v:
In Theoretical Computer Science 1 November 2024 1015
Autor:
Kanamori, Kentaro, Takagi, Takuya, Kobayashi, Ken, Ike, Yuichi, Uemura, Kento, Arimura, Hiroki
Post-hoc explanation methods for machine learning models have been widely used to support decision-making. One of the popular methods is Counterfactual Explanation (CE), also known as Actionable Recourse, which provides a user with a perturbation vec
Externí odkaz:
http://arxiv.org/abs/2012.11782
Autor:
Iwashita, Hiroaki, Takagi, Takuya, Suzuki, Hirofumi, Goto, Keisuke, Ohori, Kotaro, Arimura, Hiroki
Learning of interpretable classification models has been attracting much attention for the last few years. Discovery of succinct and contrasting patterns that can highlight the differences between the two classes is very important. Such patterns are
Externí odkaz:
http://arxiv.org/abs/2004.08015
The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a string $T$ of length $n$ has $O(n)$ nodes and edges, and the string label of each edge is encoded by a pair of positions in $T$. Thus, even
Externí odkaz:
http://arxiv.org/abs/1901.10045