CODEWITHSUNDEEP
rdecision-treerwekaj48
T. Beige
T. Beige

Reputation: 179

How to get classification values in RWeka?

can anybody explain how I get the results of each leave in a decision tree made by J48 from the RWeka package?

So for example we have this iris dataset in R:

 library(RWeka)
 m1 <- J48(Species ~ ., data = iris)
 m1

In prediction I want to use the proportion in a leave. I tried to use the package Partykit but still it looks to complicated just to get the proportion in each leave.

 library(partykit)
 pres <- as.party(m1)
 partykit:::.list.rules.party(pres)

At least I get the number of leaves in the list, but can't find the probability. 

pres

Model formula:
Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width

Fitted party:
[1] root
|   [2] Petal.Width <= 0.6: setosa (n = 50, err = 0.0%)
|   [3] Petal.Width > 0.6
|   |   [4] Petal.Width <= 1.7
|   |   |   [5] Petal.Length <= 4.9: versicolor (n = 48, err = 2.1%)
|   |   |   [6] Petal.Length > 4.9
|   |   |   |   [7] Petal.Width <= 1.5: virginica (n = 3, err = 0.0%)
|   |   |   |   [8] Petal.Width > 1.5: versicolor (n = 3, err = 33.3%)
|   |   [9] Petal.Width > 1.7: virginica (n = 46, err = 2.2%)

Number of inner nodes:    4
Number of terminal nodes: 5

So as prediction I want for example the result for a new datapoint where Petal.Width > 0.6; Petal.Width <= 1.7; Petal.Length <= 4.9 the result versicolor 97,9%. and 2,1% other. How can I get these predictions?

Upvotes: 0

Views: 204

Answers (1)

G5W
G5W

Reputation: 37641

Your point is not a point. If you fully specify a point, you can simply plug it into the predict function. For example, I will generate a point that meets the specifications, but is unlike other iris points - then classify it. 

## Generate wild new point
NewPoint = iris[1,]
NewPoint[1,3:4] = c(2.0,1.7)
NewPoint
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5            2         1.7  setosa

## Look at where the new point is
plot(iris[,3:4], pch=20, col=rainbow(3, alpha=0.3)[iris$Species])
points(NewPoint[,3:4], pch=16, col="orange")

Position of new point

## Get the probability from the model
predict(m1, newdata = NewPoint, type = "probability")
  setosa versicolor  virginica
1      0  0.9791667 0.02083333

Upvotes: 1

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