J48 is an open source Java implementation of the C4.5 algorithm in the Weka data mining tool.
Questions tagged [j48]
68 questions
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Same decision tree, different results
I work on a machine learning application and use Weka for testing, comparison classification algorithms etc. After the test operations on Weka, I determined to use J48 decision tree. I parsed the pruned tree which Weka had produced and implemented…
Anamort
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the result weka j48 classifyinstance is not correct
I already build a tree to classify the instance. In my tree, there are 14 attributes. Each attribute is discretize by supervised discrete. When I created a new instance, I put the value in this instance and classify it in my tree, and I found the…
HaoGao
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To print one confusion matrix instead of multiple matrices from each mapper
I am trying to print a confusion matrix of weka j48 algorithm and i am getting multiple matrices as output.
This is the class that runs the whole program. It is responsible for getting input from the user, setting up the mapper and reducer,…
dcoder
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How does Weka calculate Precision using J48?
I'm new to data mining and Weka. I built a classifier with J48 in Weka using the GUI. When Weka is finished running it says:
Correctly Classified Instances 1035 - 68.543 %
Incorrectly Classified Instances 475 - 31.457 %
When running from my…
Lorenzo
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J48 algorithm in weka algorithm or flowchart steps
I am new in the machine learning area. please, I was wondering if you could provide me with algorithm or flowchart steps for J48.
note: I am using the default setting in weka.
thank you for your help.
Zaid T.S
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C4.5 Decision Tree Algorithm doesn't improve the accuracy
I ran C4.5 Pruning algorithm in Weka using 10-fold cross validation. I noticed that the unpruned tree had a higher testing accuracy than a pruned tree. I couldn't understand the reason about why pruning the tree didn't improve the testing accuracy?
Dan
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how can i find training error or error(D) and test error or error(s)
I need to find training error or error(D) and test error or error(s).
hypothetically, to find error(s) we use formula : misclassified instances/total instances
then to find error(D) we use
error(s)+-confidenceInterval…
want2
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Zero-R model calculation of Sensitivity and Specificity using Confusion Matrix and Statistics with Caret
Here are my results from the confusionMatrix() function in R, this is based on a Zero-R model. I may have setup the function incorrectly, according to its results there's a mismatch between what I manually got as the answer varied by randomized…
cocoakrispies93
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