Bayesian Decision Trees

Bayesian Decision Trees is a probabilistic decision tree model that incorporates Bayesian inference to estimate posterior distributions over tree structures and parameters, distinguishing itself from classical decision trees by formally quantifying uncertainty in both predictions and tree topology through prior and posterior probabilities.

105

Publications

4.9K

Citations

300

Authors

153

Institutions

Publications per year

2017–2026

35

Authors

300

  1. VS
    Vitaly Schetinin

    University of Bedfordshire, United Kingdom

    7 publications · 191 citations

    7

    h-index

  2. WJ
    W. J. Krzanowski

    University of Exeter, United Kingdom

    6 publications · 163 citations

    6

    h-index

  3. LJ
    Livija Jakaite

    University of Bedfordshire, United Kingdom

    4 publications · 101 citations

    4

    h-index

  4. AH
    Adolfo Hernández

    Universidad Complutense de Madrid, Spain

    3 publications · 90 citations

    3

    h-index

  5. TB
    Trevor Bailey

    University of Exeter, United Kingdom

    3 publications · 90 citations

    3

    h-index

1–5 of 300

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 50 citations

    3

    h-index

  2. 2

    h-index

  3. Psychometrika

    2 publications · 408 citations

    2

    h-index

  4. Expert Systems with Applications

    2 publications · 72 citations

    2

    h-index

  5. 2

    h-index

1–5