But how does it estimate that voting output? How does it get the 85.7% for all the trees?
Regarding the prediction accuracy. If I have OOB error = 2.34, then the prediction accuracy will be equal to 76.6%, right? Many thanks, Chrysanthi. 2009/4/13 Liaw, Andy <andy_l...@merck.com> > RF forms prediction by voting. Note that each row in the output sums to > 1. It says 85.7% of the trees classified the first case as "healthy" and > the other 14.3% of the trees "unhealthy". The majority (in two-class cases > like this one) wins, so the prediction is "healthy". > > You can take 1 - OOB error rate as the estimate of prediction accuracy (if > you have not selected variables, e.g., using variable importance, in > building the final RF model). > > Andy > > ------------------------------ > *From:* Chrysanthi A. [mailto:chrys...@gmail.com] > *Sent:* Friday, April 10, 2009 10:44 AM > > *To:* Liaw, Andy > *Cc:* r-help@r-project.org > *Subject:* Re: [R] help with random forest package > > > > Hi, > > To be honest, I cannot really understand what is the meaning of the votes.. > For example having five samples and two classes what the numbers below > means? > healthy unhealthy > 1 0.85714286 0.14285714 > 2 0.92857143 0.07142857 > 3 0.90000000 0.10000000 > 4 0.92857143 0.07142857 > 5 0.84615385 0.15384615 > > Suppose now, having the classification, I have an unknown sample and > according to the results that Ive got, how can I predict in which class it > belongs to? Do the votes give that prediction to us? > > Also, the error is reported on the "OOB estimate of error rate", right? > For example, if we have OOB estimate of error rate:2.34%, we can say that > the prediction accuracy is approx. 97.7%? How can we estimate the prediction > accuracy? > > > Thanks a lot, > > Chrysanthi. > > > 2009/4/8 Liaw, Andy <andy_l...@merck.com> > >> I'm not quite sure what you're asking. RF predicts by classifying the >> new observation using all trees in the forest, and take plural vote. The >> predict() method for randomForest objects does that for you. The getTree() >> function shows you what each individual tree is like (not visually, just the >> underlying representation of the tree). >> >> Andy >> >> ------------------------------ >> *From:* Chrysanthi A. [mailto:chrys...@gmail.com] >> *Sent:* Wednesday, April 08, 2009 2:56 PM >> *To:* Liaw, Andy >> *Cc:* r-help@r-project.org >> *Subject:* Re: [R] help with random forest package >> >> Many thanks for the reply. >> >> So, extracting the votes, how can we clarify the classification result? If >> I want to predict in which class will be included an unknown sample, what is >> the rule that will give me that? >> >> Thanks a lot, >> >> Chrysanthi. >> >> >> >> 2009/4/8 Liaw, Andy <andy_l...@merck.com> >> >>> The source code of the whole package is available on CRAN. All packages >>> are submitted to CRAN is source form. >>> >>> There's no "rule" per se that gives the final prediction, as the final >>> prediction is the result of plural vote by all trees in the forest. >>> >>> You may want to look at the varUsed() and getTree() functions. >>> >>> Andy >>> >>> From: Chrysanthi A. >>> > Hello, >>> > >>> > I am a phd student in Bioinformatics and I am using the Random Forest >>> > package in order to classify my data, but I have some questions. >>> > Is there a function in order to visualize the trees, so as to >>> > get the rules? >>> > Also, could you please provide me with the code of >>> > "randomForest" function, >>> > as I would like to see how it works. I was wondering if I can get the >>> > classification having the most votes over all the trees in >>> > the forest (the >>> > final rules that will give me the final classification). >>> > Also, is there a >>> > possibility to get a vector with the attributes that are >>> > being selected for >>> > each node during the construction of each tree? I mean, that >>> > I would like to >>> > know the m<<M variables that are selected at each node out of >>> > the M input >>> > attributes.. Are they selected randomly? Is there a >>> > possibility to select >>> > the same variable in subsequent nodes? >>> > >>> > Thanks a lot, >>> > >>> > Chrysanthi. >>> > >>> > [[alternative HTML version deleted]] >>> > >>> > ______________________________________________ >>> > R-help@r-project.org mailing list >>> > https://stat.ethz.ch/mailman/listinfo/r-help >>> > PLEASE do read the posting guide >>> > http://www.R-project.org/posting-guide.html >>> > and provide commented, minimal, self-contained, reproducible code. >>> > >>> Notice: This e-mail message, together with any attachments, contains >>> information of Merck & Co., Inc. 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