Question
I need support to load the soybean diagnosis data set in Weka (found in Weka-3.6/data/soybean.arff), then perform the following: Build a decision tree by selecting
I need support to load the soybean diagnosis data set in Weka (found in Weka-3.6/data/soybean.arff), then perform the following:
Build a decision tree by selecting J48 as the classifier and 10-way cross-validation. Then fill out the following table:
Correctly Classified Instances |
|
Incorrectly Classified Instances |
|
Kappa statistic |
|
Mean absolute error |
|
Root mean squared error |
|
Relative absolute error |
|
Root relative squared error |
|
Total Number of Instances |
|
Build a Nave Bayes classifier and select 10-way cross-validation. Then fill out the following table:
Correctly Classified Instances |
|
Incorrectly Classified Instances |
|
Kappa statistic |
|
Mean absolute error |
|
Root mean squared error |
|
Relative absolute error |
|
Root relative squared error |
|
Total Number of Instances |
|
Compare between results in previous two sections (a and b), which algorithm give the better result and why?
Please write with your own words and don't copy or use handwriting.
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