yaiRFsummary

an object of class <code><a href="/link/yai?package=yaImpute&version=1.0-21" rd-options="" data-mini-rdoc="yaImpute::yai">yai</a></code>.

object

the <code>nTop</code> most important variables are plotted (returned).

nTop

When method <code>randomforest</code> is used to build a <code><a href="/link/yai?package=yaImpute&version=1.0-21" rd-options="" data-mini-rdoc="yaImpute::yai">yai</a></code>
  object, the <code><a href="/link/randomForest?package=yaImpute&version=1.0-21&to=randomForest" rd-options="randomForest" data-mini-rdoc="randomForest::randomForest">randomForest</a></code> package computes
  several statistics. This function summarizes some of them, including
  the variable importance scores computed by function <code><a href="/link/yaiVarImp?package=yaImpute&version=1.0-21" rd-options="" data-mini-rdoc="yaImpute::yaiVarImp">yaiVarImp</a></code>.

multivariate

misc

tree

Performs nearest neighbor-based imputation using one or more alternative 
 approaches to processing multivariate data. These include methods based on canonical 
 correlation analysis, canonical correspondence analysis, and a multivariate adaptation 
 of the random forest classification and regression techniques of Leo Breiman and Adele 
 Cutler. Additional methods are also offered. The package includes functions for 
 comparing the results from running alternative techniques, detecting imputation targets 
 that are notably distant from reference observations, detecting and correcting 
 for bias, bootstrapping and building ensemble imputations, and mapping results.

yaiRFsummary: Build Summary Data For Method RandomForest

Description

Usage

Arguments

Value

See Also