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Papers: 10.3390/e23050601

https://doi.org/10.3390/e23050601

Information Structures for Causally Explainable Decisions

Cited by: 3
Author(s): Louis Anthony Cox
Published: about 4 years ago

Software Mentions 9

cran: ALEPlot
Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots
Papers that mentioned: 2
Very Likely Science (83)
cran: bnlearn
Bayesian Network Structure Learning, Parameter Learning and Inference
Papers that mentioned: 113
Very Likely Science (85)
cran: CompareCausalNetworks
Interface to Diverse Estimation Methods of Causal Networks
Papers that mentioned: 1
Very Likely Science (100)
cran: npreg
Nonparametric Regression via Smoothing Splines
Papers that mentioned: 1
Very Likely Science (93)
cran: pdp
Partial Dependence Plots
Papers that mentioned: 16
Very Likely Science (95)
cran: rpart
Recursive Partitioning and Regression Trees
Papers that mentioned: 431
Very Likely Science (100)
pypi: bnlearn
Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Papers that mentioned: 113
Very Likely Science (90)
pypi: pdp
Build fast data processing pipelines easily
Papers that mentioned: 16
Likely Science (40)
pypi: Quickstart
Papers that mentioned: 9
Unlikely Science (0)