Hello everybody I'm having some difficulties to design the decision tree algorithm J48. I am using the following code and when I run it gives me the following message plot(m1) Error in plot.Weka_tree(m1) : Plotting of trees with multi-way splits is currently not implemented. #The code library(RWeka) library(randomForest) library(party) if(require(mlbench, quietly = TRUE) && require(party, quietly = TRUE)) m1 <- J48(income2 ~ age+workclass+native.country, data = dataset) m1 plot(m1) and results #M1 Results workclass = ?: <=50K (1433.0/120.0) workclass = Federal-gov: <=50K (696.0/281.0) workclass = Local-gov: <=50K (1542.0/469.0) workclass = Never-worked: <=50K (5.0) workclass = Private: <=50K (16939.0/3705.0) workclass = Self-emp-inc | age <= 36: <=50K (205.0/65.0) | age > 36: >50K (652.0/247.0) workclass = Self-emp-not-inc: <=50K (1926.0/525.0) workclass = State-gov: <=50K (1010.0/262.0) workclass = Without-pay: <=50K (13.0/2.0) Number of Leaves : 10 Size of the tree : 12 I tried installing the package RGraphviz, but is not available in CRAN repository. I wonder if there is a package that lets you draw decision trees in a way more effective than the library(party) which the classification algorithms more efficient in R Thanks -- View this message in context: http://r.789695.n4.nabble.com/libary-Rweka-J48-design-tree-tp4037704p4037704.html Sent from the R help mailing list archive at Nabble.com.
libary(Rweka) J48 design tree
2 messages · RMSOPS, Achim Zeileis
On Sun, 13 Nov 2011, RMSOPS wrote:
Hello everybody I'm having some difficulties to design the decision tree algorithm J48. I am using the following code and when I run it gives me the following message plot(m1) Error in plot.Weka_tree(m1) : Plotting of trees with multi-way splits is currently not implemented.
The package "partykit" which recently was released to CRAN should be able
to help here:
library("partykit")
plot(as.party(m1))
Furthermore, write_to_dot(m1, "m1.dot") can always be used as described in
Kurt Hornik, Christian Buchta, Achim Zeileis (2009) Open-Source
Machine Learning: R Meets Weka. Computational Statistics, 24(2),
225-232. doi:10.1007/s00180-008-0119-7
Either use Graphviz directoy on the .dot file or employ Rgraphviz which is
hosted at Bioconductor:
http://www.Bioconductor.org/packages/release/bioc/html/Rgraphviz.html
#The code library(RWeka) library(randomForest) library(party) if(require(mlbench, quietly = TRUE) && require(party, quietly = TRUE)) m1 <- J48(income2 ~ age+workclass+native.country, data = dataset) m1 plot(m1) and results #M1 Results workclass = ?: <=50K (1433.0/120.0) workclass = Federal-gov: <=50K (696.0/281.0) workclass = Local-gov: <=50K (1542.0/469.0) workclass = Never-worked: <=50K (5.0) workclass = Private: <=50K (16939.0/3705.0) workclass = Self-emp-inc | age <= 36: <=50K (205.0/65.0) | age > 36: >50K (652.0/247.0) workclass = Self-emp-not-inc: <=50K (1926.0/525.0) workclass = State-gov: <=50K (1010.0/262.0) workclass = Without-pay: <=50K (13.0/2.0) Number of Leaves : 10 Size of the tree : 12 I tried installing the package RGraphviz, but is not available in CRAN repository. I wonder if there is a package that lets you draw decision trees in a way more effective than the library(party) which the classification algorithms more efficient in R Thanks -- View this message in context: http://r.789695.n4.nabble.com/libary-Rweka-J48-design-tree-tp4037704p4037704.html Sent from the R help mailing list archive at Nabble.com.
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