In order to get credit for the course, hand in (via email to
ut.ee) the following by the 24th of December:
- Lab 1: Frequent Itemsets
- Implementation of the frequent itemset mining algorithm (working code).
- Written answers to the following questions (slides 9 and 10):
- Given a fixed itemset i, devise a permutation test, to see whether it is significant.
- If a fixed itemset is present is this frequent in a given dataset, how likely is it going to be present in another transaction?
- What about a discovered itemset?
- Lab 2: Regularization, Nonlinear Regression
- Conclusions derived from Exercises 1, 2 and 4, in written form.
- The code and a brief conslusion (in written form) for Exercise 7.
- Exercise 9: Code (a. and b.) and a written answer to c.
- Lab 3: PCA, K-means
- The code and the scatterplot from Exercise 5.
- The code and a written summary for Exercise 7.
- Home Assignment: CCA, Cross-language Text Retrieval
- Code and written summary for Exercises 4 and 5.