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Random forests use a bootstrapping approach, where a random set of predictor variables is tested at each split of a tree. The final regression model results from averaging all outputs of the decision tree ensemble. Random forests are relatively robust against overfitting and multi-collinearity, ...
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The shaded area represents a 95% confidence interval, estimated based on 1,000 bootstraps. (c) The fraction of genes with a recent transfer event (that is involving gene pairs with ≥98% nucleotide identity) detected compared across species’ preferred environments, with *** indicating a ...
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Bootstrap support values are from maximum-parsimony analyses of 1,000 bootstrap replicates and 100 random addition replicates. Posterior probability for clade support was estimated with Markov chain Monte Carlo as implemented in MrBayes. Four Markov chains were run for 105 to 106 generations after ...
an important aspect is the reconciliation of gene and species trees. Multiple reconciliations may exist that may be optimal (i.e. most parsimonious). Therefore, it is important to traverse through the entire solution search space and to produce quantitative indicators (similar to bootstrap support ...
One-way ANOVA with a trimming level of 0.2 and 1000 bootstrap samples [32] was non-significant (p = 0.61). Figure 12A presents boxplot of errors for different working distances. To investigate the effect of length of the target object on general horizontal measurement in the uniform model,...