Sentence examples for outcome tree from inspiring English sources

The outcome tree for HAV disease progression was adopted from that developed as part of the Burden of Communicable Disease in Europe (BCoDE) project [ 16].

Likelihood-based approaches have proven especially powerful for inferring phylogenetic trees [ 1, 2] but are computationally expensive owing both to the form of the likelihood function itself, and to the need to search the multidimensional space of possible outcomes (tree space) for optimal trees.

We carried out a study to: 1) explore the rationale of farmers to maintain on-farm trees beyond crop yield; 2) quantify the impact of agronomic practices on the outcome of tree-crop interactions; and 3) analyse partial economic trade-offs for selected on-farm tree species at farm scale.

Two original research pieces – both about the outcomes of tree planting, with similar research designs, both published in January 2018 (Whitburn et al. in Environment and Behavior, and Watkins et al. in Cities) – cite precisely zero journal articles in common.

To characterize outcomes of tree competition along an edaphic resource gradient, we quantified variation in height and crown allometries of six Bornean tree species from contrasting regeneration niches (light-demanding vs. shade-tolerant) on two soil habitats (clay-fine loam and sandy loam) within a 52-ha forest dynamics plot.

Whereas some methods, such as linear regression, often default to only using complete data to predict an outcome, decision trees use the surrogate split method.

Therefore, we defined a dichotomous clinical outcomes decision tree, in which early relapse equates to disease free survival time ≤ 2 years, and late relapse to DFS time ≥ 8 years (defined in this manner the data set contains 92 early relapse and 211 late relapse patients).

In our models, architectural decision topic groups, issues, alternatives, and outcomes form trees of nodes connected by edges expressing containment and refinement, decomposition, and triggers dependencies, as well as logical relations such as (in compatibility of alternatives.

Catastrophic yet very rare outcomes might, by their values alone, substantially influence decision tree outcome.

The new approach is based on the observation that probability of the correct tree outcome is different in various tree sections.

The outcome of the tree reconstruction varies with the chosen method to cope with the bias.