ABSTRACT: We elaborate on an alternative representation of conditional probability to the usual tree diagram. We term the representation “turtleback diagram” for its resemblance to the pattern on ...

We consider the problem of estimating the conditional probability of a label in time O(log n), where n is the number of possible labels. We analyze a natural reduction of this problem to a set of ...

In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability ...

In decision modeling with influence diagrams, the most challenging task is probability elicitation from domain experts. It is usually very difficult for experts to directly assign precise ...

For cutting-edge AI researchers looking for clean semantics models to represent the context-specific causal dependencies essential for causal induction, this DeepMind’s algorithm encourages you to ...

Abstract: Decision tree algorithm is a very active research area of data mining. This paper describes the basic decision tree idea in data mining, then discusses the computational complexity of the ...

<a href="https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library/binomial-random-variables/v/binomial-distribution">Binomial ...