CTree

[…] The conditional inference tree for classification was built using the ctree function from the party R package with default parameters. Genes with a background mutation frequency >5 × 10−4 were excluded to avoid artifacts. The following variables were fed into the model […]

[…] e-specific numeric scales where N and λ could range from 0 to ∞ and φ could range from 0 to 1.We used the same training data sets and explanatory variables as our variable importance analysis and the ctree function in the R package party [] to grow separate classification trees for each set of predictor variables for the TRB and UARB. We converted the EXTANT variable from the variable importance d […]

[…] ke information criterion (AIC). Their DA was assessed through their areas under the receiver-operating-characteristic (ROC) curves (AUCs) along with their 95% CI.We then fitted a classification tree (CTREE or conditionally unbiased inference classification tree), a relatively new and useful predictive technique for studying RFs and outcomes based on the unbiased recursive splitting of the study po […]

[…] he RF models characterised by a good prediction performance and enabled to identify the range of the morphometric ratios values associated with each sex and/or maturity stage of male and female. The ‘ctree’ function for conditional inference trees in the ‘party’ R package (Hothorn et al. ) was used. Live fish (males) were then used to test if the trade-off values of the morphometric ratios identif […]

[…] In both CART and CTree, splitting continues until a stopping rule triggers. In CART, splitting stops when the relative reduction in error resulting from the best split falls below a pre-specified threshold known as th […]

[…] ees []. Conditional inference trees recursively perform univariate splits [] of the dependent variable based on values of different covariates. Conditional inference trees were constructed using the “ctree” function from the R package Party version 1.0–21 [] with statistics software R version 3.3.1. These non-parametric regression trees can be used for nominal, ordinal, numerical, censored and mul […]