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A heuristic search method with tree-bisection-reconnection branch swapping and one hundred replicates was used.

For each analysis, preliminary maximum parsimony searches were conducted using heuristic search methods with tree bisection reconnection (TBR) branch swapping, collapse of zero-length branches, all characters weighted equally, and 100 replicates of the random addition starting tree option.

Secondly, we define a framework that combines the MCMC-PBPA method with decision tree analysis in order to calculate the VOI.

We compare the performance of our method with existing tree tanglegram algorithms and also show a typical application to real biological datasets.

Using a single sequence for each OTU, evolutionary distances were calculated with the Jukes-Cantor (tree-Markov) model and phlyogenetic trees determined by the Neighbour-Joining method, with 1000 trees generated.

Savic et al. focus on the problem of indoor positioning and propose to enhance the well-known nonparametric belief propagation (NBP) method with spanning trees (NBP-ST).

There was no material bias with parametric MICE (mean hazard ratio = 0.806) or our random forest MICE method with 10 trees ("MICE RF 10"; mean hazard ratio = 0.807).

MP analysis was performed with a heuristic search using close neighbor interchange (level = 1), a branch-swapping method with initial trees generated by random addition (10 replications); a complete deletion option was used to treat gaps/missing data.

The best set of parameters for Rotation Forest technique was Random Forest as the tree based method with 50 decision trees, 5 features for random selection and 7 as the maximum depth.

We settled some options of the inversion method with sensitivity studies: tree covers are simulated with 4-tree scenes, expression h has six coefficients ci and the interpolation is the continuous first derivative interpolation method.

The orthologous relationship was inferred by the TBLASTN reciprocal best-hit method with further gene trees and species trees reconciliation.

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