public:t-622-arti-12-1:lab_5_-_learning_decision_trees
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| public:t-622-arti-12-1:lab_5_-_learning_decision_trees [2012/03/15 13:14] – stephan | public:t-622-arti-12-1:lab_5_-_learning_decision_trees [2024/04/29 13:33] (current) – external edit 127.0.0.1 | ||
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| - Plot the learning curves for all three data sets (monk-1, monk-2, monk-3) and interpret them. | - Plot the learning curves for all three data sets (monk-1, monk-2, monk-3) and interpret them. | ||
| - Are the trees that are learned consistent with the training data? If not, what could be the reason? | - Are the trees that are learned consistent with the training data? If not, what could be the reason? | ||
| + | - Look at the true functions for the three data sets in monk.names (Section 9). Design a good decision tree for each of the concepts by hand. | ||
| + | - Compare these decision trees to the ones that were learned by the algorithm (on the whole training data). | ||
| + | |||
| Hand In: | Hand In: | ||
| - Learning curves for the three data sets. | - Learning curves for the three data sets. | ||
| - Interpretation of the learning curves. | - Interpretation of the learning curves. | ||
| - | + | - Answer to 3. | |
| + | - Decision trees for 4. | ||
| + | - Interpretation of your findings for 5. | ||
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