Search Results for author: Mário Popolin Neto

Found 2 papers, 0 papers with code

Multivariate Data Explanation by Jumping Emerging Patterns Visualization

no code implementations21 Jun 2021 Mário Popolin Neto, Fernando V. Paulovich

Visual Analytics (VA) tools and techniques have been instrumental in supporting users to build better classification models, interpret models' overall logic, and audit results.

Classification Descriptive

Explainable Matrix -- Visualization for Global and Local Interpretability of Random Forest Classification Ensembles

no code implementations8 May 2020 Mário Popolin Neto, Fernando V. Paulovich

In this paper, we propose Explainable Matrix (ExMatrix), a novel visualization method for RF interpretability that can handle models with massive quantities of rules.

General Classification

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