Search Results for author: Hiroshi Tokieda

Found 2 papers, 1 papers with code

A copula-based visualization technique for a neural network

1 code implementation27 Mar 2020 Yusuke Kubo, Yuto Komori, Toyonobu Okuyama, Hiroshi Tokieda

Interpretability of machine learning is defined as the extent to which humans can comprehend the reason of a decision.

Decision Making Feature Importance

Model Bridging: Connection between Simulation Model and Neural Network

no code implementations22 Jun 2019 Keiichi Kisamori, Keisuke Yamazaki, Yuto Komori, Hiroshi Tokieda

One approach is replacing the un-interpretable machine learning model with a surrogate model, which has a simple structure for interpretation.

BIG-bench Machine Learning Decision Making +1

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