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POSearch for corresponding node in a regression tree using rpart
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copied!<p>I'm pretty new to R and I'm stuck with a pretty dumb problem.</p> <p>I'm calibrating a regression tree using the <strong>rpart</strong> package in order to do some classification and some forecasting.</p> <p>Thanks to R the calibration part is easy to do and easy to control.</p> <pre><code>#the package rpart is needed library(rpart) # Loading of a big data file used for calibration my_data <- read.csv("my_file.csv", sep=",", header=TRUE) # Regression tree calibration tree <- rpart(Ratio ~ Attribute1 + Attribute2 + Attribute3 + Attribute4 + Attribute5, method="anova", data=my_data, control=rpart.control(minsplit=100, cp=0.0001)) </code></pre> <p>After having calibrated a big decision tree, I want, for a given data sample to find the corresponding cluster of some new data (and thus the forecasted value).<br> The <code>predict</code> function seems to be perfect for the need.</p> <pre><code># read validation data validationData <-read.csv("my_sample.csv", sep=",", header=TRUE) # search for the probability in the tree predict <- predict(tree, newdata=validationData, class="prob") # dump them in a file write.table(predict, file="dump.txt") </code></pre> <p>However with the <code>predict</code> method I just get the forecasted ratio of my new elements, and I can't find a way get the <strong>decision tree leaf</strong> where my new elements belong.</p> <p>I think it should be pretty easy to get since the predict method <strong>must</strong> have found that leaf in order to return the ratio.</p> <p>There are several parameters that can be given to the predict method through the <code>class=</code> argument, but for a regression tree all seem to return the same thing (the value of the target attribute of the decision tree)</p> <p>Does anyone know how to get the corresponding node in the decision tree?</p> <p>By analyzing the node with the <code>path.rpart</code> method, it would help me understanding the results.</p>

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