Liaw, Andy
2005-Mar-23 00:25 UTC
[R] Error: Can not handle categorical predictors with more th an 32 categories.
It always helps to check whether you got the data into R correctly. Hint: What does str(credit) tell you? Andy> From: Melanie Vida > > Hi All, > > My question is in regards to an error generated when using > randomForest > in R. Is there a special way to format the data in order to > avoid this > error, or am I completely confused on what the error implies? > > "Error in randomForest.default(m, y, ...) : > Can not handle categorical predictors with more than > 32 categories." > > This is generated from the command line: > > credit.rf <- randomForest(V16 ~ ., data=credit, mtry=2, > importance = > TRUE, do.trace=100) > > The data set is the credit-screening data from the UCI respository, > ftp://ftp.ics.uci.edu/pub/machine-learning-databases/credit-screening/crx.data. This data consists of 690 samples and 16 attributes. The attribute information includes: A1: b, a. A2: continuous. A3: continuous. A4: u, y, l, t. A5: g, p, gg. A6: c, d, cc, i, j, k, m, r, q, w, x, e, aa, ff. A7: v, h, bb, j, n, z, dd, ff, o. A8: continuous. A9: t, f. A10: t, f. A11: continuous. A12: t, f. A13: g, p, s. A14: continuous. A15: continuous. A16: +,- (class attribute) Has anyone tried randomForests in R on the credit-screening data set from the UCI repository? Thanks in advance for any useful hints and tips, Melanie ______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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