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2020
In this chapter, for complexity functions having the properties \(\varLambda 1 \), \(\varLambda 2\), and \(\varLambda 3\), upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called difference-bounded uncertainty
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In this chapter, for complexity functions having the properties \(\varLambda 1 \), \(\varLambda 2\), and \(\varLambda 3\), upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called difference-bounded uncertainty
openaire +1 more source
Efficient Modeling of Deterministic Decision Trees for Recognizing Realizable Decision Rules
Kerven Durdymyradov +2 moreopenaire +1 more source
Decision aids for localized prostate cancer treatment choice: Systematic review and meta-analysis
Ca-A Cancer Journal for Clinicians, 2015Arnav Agarwal, Henrikki Santti
exaly
Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity Local Approach
Lecture Notes in Computer Science, 2005Mikhail Ju Moshkov
exaly
Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity.
Fundam. Informaticae, 1996openaire +1 more source
What is lacking in current decision aids on cancer screening?†
Ca-A Cancer Journal for Clinicians, 2013Sarah T Hawley, Donald E Nease
exaly
Implementing and evaluating shared decision making in oncology practice
Ca-A Cancer Journal for Clinicians, 2014Linda B Squiers +2 more
exaly
Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity. Global Approach
Kerven Durdymyradov +2 moreopenaire +1 more source
Time and Space Complexity of Deterministic and Nondeterministic Decision Trees. Global Approach
Kerven Durdymyradov +2 moreopenaire +1 more source