Differences

This shows you the differences between two versions of the page.

--- public:t-622-arti-13-1:lab_6_-_learning_decision_trees [2013/03/19 12:54] – stephan
+++ public:t-622-arti-13-1:lab_6_-_learning_decision_trees [2024/04/29 13:33] (current) – external edit 127.0.0.1
@@ Line 2: / Line 2: @@
 Material:
-  * {{:public:t-622-arti-12-1:dtl_learning.zip|java project}}
+  * {{:public:t-622-arti-13-1:dtl_learning.zip|java project}}
   * [[http://aima-java.googlecode.com/svn/trunk/aima-all/release/javadoc/aima-core/index.html|javadoc for the framework]]
+The zip archive contains three data sets and Java code to learn a decision tree from those data sets. Your task is to check how well the learning algorithm performs on the given data sets.
 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 test each of the trees using the test set.
+  - 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.
-  - Plot the learning curves for all three data sets (e.g., using MS Excel, LibreOffice, Google Docs, ...) (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) (monk-1, monk-2, monk-3) and interpret them.
-  - Are all the trees that are learned consistent with the training data? If not, what could be the reason?
+  - 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 a good decision tree for the concept of monks-1 by hand.
   - Compare this decision trees to the one that was learned by the algorithm using the whole training set.
@@ Line 17: / Line 19: @@
   - Interpretation of the learning curves.
   - Answer to 3.
-  - Decision trees for 4.
+  - Decision tree for 4.
   - Interpretation of your findings for 5.