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PONew factor levels not present in the training data
 

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    <p>When trying to use the output of <code>randomForest</code> to classify new data (or even the original training data), I get the following error:</p> <pre><code>&gt; res.rf5 &lt;- predict(model.rf5, train.rf5) Error in predict.randomForest(model.rf5, train.rf5) : New factor levels not present in the training data </code></pre> <p>What does this error mean? Why does this error occur even when I try to predict the same data I used to train?</p> <p>A small example that can be used to reproduce the error is below.</p> <pre><code>train.rf5 &lt;- structure( list(A = structure(c(2L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 3L), .Label = c("(-0.1,19.9]", "(19.9,40]", "(80.1,100]"), class = c("ordered", "factor")), B = structure(c(3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 4L), .Label = c("1", "2", "4", "5"), class = c("ordered", "factor")), C = structure(c(1L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L), .Label = c("FALSE", "TRUE"), class = "factor")), .Names = c("A", "B", "C"), row.names = c(7L, 8L, 10L, 11L, 13L, 15L, 16L, 17L, 18L, 19L), class = "data.frame") # A B C # 7 (19.9,40] 4 FALSE # 8 (-0.1,19.9] 1 FALSE # 10 (-0.1,19.9] 1 TRUE # 11 (-0.1,19.9] 1 FALSE # 13 (-0.1,19.9] 1 FALSE # 15 (-0.1,19.9] 1 TRUE # 16 (80.1,100] 2 TRUE # 17 (-0.1,19.9] 1 FALSE # 18 (-0.1,19.9] 1 FALSE # 19 (80.1,100] 5 TRUE require(randomForest) model.rf5 &lt;- randomForest(C ~ ., data = train.rf5) res.rf5 &lt;- predict(model.rf5, train.rf5) # Causes error </code></pre> <p>I see some possibly related questions on SO, but I don't think they solve my issue directly</p> <ol> <li><a href="https://stackoverflow.com/questions/1195826/dropping-factor-levels-in-a-subsetted-data-frame-in-r" title="dropping factor levels in a subsetted data frame in R">dropping factor levels in a subsetted data frame in R</a></li> <li><a href="https://stackoverflow.com/questions/17059432/random-forest-package-in-r-shows-error-during-prediction-if-there-are-new-fact">Random forest package in R shows error during prediction() if there are new factor levels present in test data. Is there any way to avoid this error?</a></li> </ol> <p>Unlike 1), I do not have factor levels that are not represented in the data, and unlike 2), the factor levels in my train and test data are identical.</p> <p>Edit: Additional information:</p> <pre><code>sessionInfo() R version 3.0.1 (2013-05-16) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] randomForest_4.6-7 loaded via a namespace (and not attached): [1] tools_3.0.1 </code></pre>
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    1. COI'll bet it has something to do with the ordered factors.
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