Error In Na.fail.default Missing Values In Object Random Forest
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here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this random forest missing values site About Us Learn more about Stack Overflow the company Business Learn error in na.fail.default lme more about hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question rfimpute x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up How lme missing values in object to build random forests in R with missing (NA) values? up vote 41 down vote favorite 21 I would like to fit a random forest model, but when I call library(randomForest) cars$speed[1] <- NA # to simulate missing value model <- randomForest(speed ~., data=cars) I get the following error Error in na.fail.default(list(speed = c(NA, 4, 7, 7, 8, 9, 10, 10, 10, : missing
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values in object r machine-learning random-forest na missing-data share|improve this question edited Oct 27 '15 at 5:47 smci 7,36543777 asked Dec 3 '11 at 19:44 Borut Flis 2,543144881 In it's current state, this question will be very difficult to answer. Can you update your question with some sample data? –Chase Dec 3 '11 at 23:05 6 Amusing to note that something that is "not a real question" has close to 10,000 views as of March 2014 –Matt O'Brien Mar 21 '14 at 19:30 @MattO'Brien Also amusing that the quality of a question is discussed based on viewcount and not on the merits of the question itself. And the answer, since @ Joran had no problem figuring out what is being asked and provided what appears to be a good solution for the asker's problem. –user7610 Jul 25 '14 at 14:57 add a comment| 1 Answer 1 active oldest votes up vote 74 down vote accepted My initial reaction to this question was that it didn't show much research effort, since "everyone" knows that random forests don't handle missing values in predictors. But upon
forest but when I create the model error in randomforest.default(m, y, ...) : na/nan/inf in foreign function call (arg 1) of random forest it gives me error which says error in getgroups.data.frame(datamix, groups) : invalid formula for groups missing value in object.head of train data Screenshot (18).png1366x768 23 KB m1<-randomForest(as.factor(Survived)~.,data=train)Error in na.fail.default(list(`as.factor(Survived)` = c(1L, http://stackoverflow.com/questions/8370455/how-to-build-random-forests-in-r-with-missing-na-values 2L, 2L, 2L, : missing values in object shuvayan 2015-08-23 09:04:20 UTC #2 Hello @hinduja1234, One of the requirements that the data must satisfy before running a random forest is that there must https://discuss.analyticsvidhya.com/t/how-to-remove-the-missing-value-of-object-in-random-forest/3131 not be any missing values in the data.So you can either use the package rpart which can handle missing values or do one among these 3 things:1.If there are a few records containing missing values you can drop them from the data set.2.If it is continuous variable then you can predict the values.3.Use the na.roughfix,rfImpute functions in the random forest package itself to impute the missing values.Hope this helps! Home Categories FAQ/Guidelines Terms of Service Privacy Policy Powered by Discourse, best viewed with JavaScript enabled Home Blog Jobs DataHack Trainings Learning Paths Forget Password j
Open this post in threaded view ♦ ♦ | Report Content as Inappropriate ♦ ♦ How to deal with missing values when using Random Forrest I am using the package Random Forrest to test and train a model, I aim to predict (LengthOfStay.days),: > library(randomForest) > model <- randomForest( LengthOfStay.days~.,data = training, + importance=TRUE, + keep.forest=TRUE + ) This is a small portion of the data frame: http://r.789695.n4.nabble.com/How-to-deal-with-missing-values-when-using-Random-Forrest-td4421254.html data(training)LengthOfStay.days CharlsonIndex.numeric DSFS.months 1 0 https://stat.ethz.ch/pipermail/r-help/2012-February/304757.html 0.0 8.5 6 0 0.0 3.5 7 0 0.0 0.5 8 0 0.0 0.5 9 error in 0 0.0 1.5 11 0 1.5 NaN Error messageError in na.fail.default(list(LengthOfStay.days = c(0, 0, 0, 0, 0, 0, : missing values in object, I would greatly appreciate any help Thanks Kevin David Winsemius Threaded Open this post in threaded view ♦ ♦ | Report Content as Inappropriate ♦ ♦ Re: How to deal with missing values when using Random Forrest On Feb 25, 2012, at 6:24 PM, kevin123 wrote: error in na.fail.default > I am using the package Random Forrest to test and train a model, > I aim to predict (LengthOfStay.days),: > >> library(randomForest) >> model <- randomForest( LengthOfStay.days~.,data = training, > + importance=TRUE, > + keep.forest=TRUE > + ) > > > *This is a small portion of the data frame: * > > *data(training)* > > LengthOfStay.days CharlsonIndex.numeric DSFS.months > 1 0 0.0 8.5 > 6 0 0.0 3.5 > 7 0 0.0 0.5 > 8 0 0.0 0.5 > 9 0 0.0 1.5 > 11 0 1.5 NaN > > *Error message* > > Error in na.fail.default(list(LengthOfStay.days = c(0, 0, 0, 0, 0, > 0, : > missing values in object, What part of that error message is unclear? Have you looked at the randomForest page? It tells you what the default behavior is na.fail. > > I would greatly appreciate any help I would seem that the way forward is to remove the cases with missing values or to impute values. -- David Winsemius, MD Heritage Laboratories West Hartford, CT ______________________________________________ [hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code. Weidong Gu-2 Threaded
NAs in C Messages sorted by: [ date ] [ thread ] [ subject ] [ author ] Hi, You can set na.action=na.roughfix which fills NAs with the mean or mode of the missing variable. Other option is to impute missing values using rfImpute, then run randomForest on the complete data set. Weidong Gu On Sat, Feb 25, 2012 at 6:24 PM, kevin123