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 Naïve 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?
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 Naïve 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?
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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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 Naïve 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?
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