Impute Missing Values by median/mode.
a data frame or numeric matrix.
further arguments special methods could require.
A completed data matrix or data frame. For numeric variables,
NAs are replaced with column medians. For factor variables,
NAs are replaced with the most frequent levels (breaking ties
at random). If
object contains no
NAs, it is returned
This is used as a starting point for imputing missing values by random forest.
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randomForest 4.6-12 Type rfNews() to see new features/changes/bug fixes. Call: randomForest(formula = Species ~ ., data = iris.na, na.action = na.roughfix) Type of random forest: classification Number of trees: 500 No. of variables tried at each split: 2 OOB estimate of error rate: 4.67% Confusion matrix: setosa versicolor virginica class.error setosa 50 0 0 0.00 versicolor 0 46 4 0.08 virginica 0 3 47 0.06
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