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_liaw@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:chrysain@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_liaw@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]]
>> >
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