Construct an explainable nomogram for a machine learning (ML) model to improve availability of an ML prediction model in addition to a computer application, particularly in a situation where a computer, a mobile phone, an internet connection, or the application accessibility are unreliable. This package enables a nomogram creation for any ML prediction models, which is conventionally limited to only a linear/logistic regression model. This nomogram may indicate the explainability value per feature, e.g., the Shapley additive explanation value, for each individual. However, this package only allows a nomogram creation for a model using categorical without or with single numerical predictors. Detailed methodologies and examples are documented in our vignette, available at <https://htmlpreview.github.io/?https://github.com/herdiantrisufriyana/rmlnomogram/blob/master/doc/ml_nomogram_exemplar.html>.
Package details |
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Author | Herdiantri Sufriyana [aut, cre] (<https://orcid.org/0000-0001-9178-0222>), Emily Chia-Yu Su [aut] (<https://orcid.org/0000-0003-4801-5159>) |
Maintainer | Herdiantri Sufriyana <herdi@nycu.edu.tw> |
License | MIT + file LICENSE |
Version | 0.1.2 |
Package repository | View on CRAN |
Installation |
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