Simply implement of C4.5 By Java
you can try use cd to get in to the file folder.
And then java -jar xxx.jar to run the corresponding program.
TrainWithoutPrune.jar Build the model without prune.
TrainWithPrune.jar Build the model with prune.
Validate.jar get the accuracy based on current tree model.
Test.jar get the prediction of the btest.csv and ouput as output_btest.csv
Also, you can modify the parameter in myConfiguration.properties
Properties in myConfiguration.properties.
#####ACCURACY
This the condition to terminate the tree, if current information entropy is smaller than this value, then terminate.
#####DISCRETE_THRESHOLD This is variable to judge the value is discrete or not. The program will build a map, and if the category of the attrubute value which is smaller than this threshold is discrete otherwise it is continuous.
#####TRAINFILE
training file name.
#####VALIDATEFILE validate filename
#####TestFILE
test filename.
#####ModelName
the model name
#####TRAININGSIZE
this will work in prune tree. generate the tree with Trainsize * DataSize data
#####learnigsize
determine to use how many data to get the tree model.
#####isPruendModel determine to use the prune model or not. it will only useful if the current pruning model is generated.
currently the whole model is built and you can use this as you want.
If you want to print the tree, please import the folder into eclipse. And you can print the tree as following steps.
- find the Train.java.
- uncommented TreeTools.printTree(node); and run it, you will see a tree.
- also if you want to see dnf just uncommented TreeTools.printDNF(node);