r - How can I access Classification Decision Tree result and confusion matrix result? -


this general iris modeling code , result: 

    general iris modeling code , result:       > library(party)     > library(rpart)     > library(tree)     > library(caret)     > train = sample(1:nrow(iris),nrow(iris)* 0.7)     > training_set = iris[train,]     > test_set = iris[-train,]     > iris_ctree = ctree(species~., data = training_set)     > iris_ctree           conditional inference tree 4 terminal nodes      response:  species      inputs:  sepal.length, sepal.width, petal.length, petal.width      number of observations:  105       1) petal.length <= 1.9; criterion = 1, statistic = 97.056       2)*  weights = 30      1) petal.length > 1.9       3) petal.width <= 1.7; criterion = 1, statistic = 48.636         4) petal.length <= 4.7; criterion = 0.998, statistic = 12.282           5)*  weights = 36          4) petal.length > 4.7           6)*  weights = 7        3) petal.width > 1.7         7)*  weights = 32      > plot(iris_ctree)     > pred = predict(iris_ctree, test_set)     > confusionmatrix(pred, test_set$species)     confusion matrix , statistics                  reference     prediction   setosa versicolor       setosa         20          0       versicolor      0         10       virginica       0          0                 reference     prediction   virginica       setosa             0       versicolor         1       virginica         14      overall statistics                     accuracy :                      95% ci :         no information rate :         p-value [acc > nir] :                        kappa :      mcnemar's test p-value :       0.9778                (0.8823, 0.9994)      0.4444                8.12e-15               0.9655                na                    statistics class:                           class: setosa     sensitivity                 1.0000     specificity                 1.0000     pos pred value              1.0000     neg pred value              1.0000     prevalence                  0.4444     detection rate              0.4444     detection prevalence        0.4444     balanced accuracy           1.0000                          class: versicolor     sensitivity                     1.0000     specificity                     0.9714     pos pred value                  0.9091     neg pred value                  1.0000     prevalence                      0.2222     detection rate                  0.2222     detection prevalence            0.2444     balanced accuracy               0.9857                          class: virginica     sensitivity                    0.9333     specificity                    1.0000     pos pred value                 1.0000     neg pred value                 0.9677     prevalence                     0.3333     detection rate                 0.3111     detection prevalence           0.3111     balanced accuracy              0.9667

  1. i want know how access specific node values of 'ctree'. example, approach value of '7', lowest branch.

  2. and want know how approach value of confusion matrix. example, approach accuracy value.

the reason question have model various data in database r , result. appreciate if give me hint.

i found answer. can reference contents.

@extract data ctree

http://rpubs.com/kkweon/294613

how extract tree structure ctree function?

@extract data confusion matrix

https://artax.karlin.mff.cuni.cz/r-help/library/caret/html/confusionmatrix.html


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