Question: Course: Data Mining and Data Warehousing Code: IT446 Load the soybean diagnosis data set in Weka (found in Weka-3.6/data/soybean.arff), then perform the following: a) Build
Course: Data Mining and Data Warehousing
Code: IT446
Load the soybean diagnosis data set in Weka (found in Weka-3.6/data/soybean.arff), then perform the following:
a) 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 |
|
b) 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 |
|
c) Compare between results in previous two sections (a and b), which algorithm give the better result and why?
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