Description
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UCI ML Repository contains many datasets for classification. You need to find 5 datasets with at least 10 attributes
https://archive.ics.uci.edu/ml/datasets.php
Complete the following tables and calculate accuracy using (1) Use 10 x 10 Fold CV (ii) 70% Holdout approach repeated 100 times
Show all the standard deviations in the table. Briefly discuss advantages / disadvantages of hold out and cross validation approach. Analysis the result. Which approach is good and why? Why some approaches unable to perform well in some data sets.
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Dataset1 Dataset2
Dataset3
Dataset4
Dataset5
DT using gini
(without pruning)
DT using gini
(with pruning)
DT using entropy
(without pruning)
DT using entropy
(with pruning)
Hint: Check ccp_alpha parameter for pruning. Use ccp_alpha = 0.015 for pruning
