public:t-622-arti-14-1:lab_6_-_learning_decision_trees
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| public:t-622-arti-14-1:lab_6_-_learning_decision_trees [2014/03/12 08:23] – created stephan | public:t-622-arti-14-1:lab_6_-_learning_decision_trees [2024/04/29 13:33] (current) – external edit 127.0.0.1 | ||
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| Tasks: | Tasks: | ||
| - | - Change the existing code, so that it prints the necessary data for a learning curve. That is, change the code such that it learns trees for increasing numbers of training examples and test each of the trees using the test set. | + | - Change the existing code (changing the main method should do), so that it prints the necessary data for a learning curve to standard output. That is, change the code such that it learns trees for increasing numbers of training examples and test each of the trees using the test set. |
| - | - Plot the learning curves for all three data sets (e.g., using a spreadsheet application of your choice) (monk-1, monk-2, monk-3) and interpret them. | + | - Plot the learning curves for all three data sets (e.g., using a spreadsheet application of your choice) and interpret them. |
| - Are all the trees that are learned consistent with the training data (consistent = all examples are classified correctly)? If not, what could be the reason? (Hint: Consistency of the tree with the training set can be checked easily by adding a single line of code.) | - Are all the trees that are learned consistent with the training data (consistent = all examples are classified correctly)? If not, what could be the reason? (Hint: Consistency of the tree with the training set can be checked easily by adding a single line of code.) | ||
| - | - Look at the true functions for the three data sets in monk.names (Section 9). Design | + | - Look at the true functions for the three data sets in monk.names (Section 9 of the file). These are the functions that were used to generate the training and test data. Now that you know the function, design |
| - | - Compare this decision trees to the one that was learned by the algorithm using the whole training set. | + | - Compare this decision trees to the one that was learned by the algorithm using the whole training set and explain the difference. |
/var/www/cadia.ru.is/wiki/data/attic/public/t-622-arti-14-1/lab_6_-_learning_decision_trees.1394612635.txt.gz · Last modified: 2024/04/29 13:32 (external edit)