Description
Implement (in C++) the Candidate Elimination algorithm (chapter 2 of [Mitchell, 1997]). Use the training examples in table 1 to verify that it correctly produces the following hypothesis for learning concept Japanese Economy Car (lecture 3):
< Japan, ?, ?, ?, Economy > Q1: Now change the training examples given in table 1 so as the candidate elimination algorithm learns the following hypothesis:
< Japan, ?, ?, ?, Sports >
Q2: What is the minimum number of training examples to learn this concept (Japanese Sports Car)?
In a ZIP file, place the source code, executable, and a text file containing your list of training examples (answers to Q1 and Q2). Upload ZIP file to the open assignment on Vula.
1
Table 1: Training examples for target concept Japanese Economy Car.
| Origin | Manufacturer | Colour | Decade | Type | Label |
| Japan | Honda | Blue | 1980 | Economy | Positive |
| Japan | Toyota | Green | 1970 | Sports | Negative |
| Japan | Toyota | Blue | 1990 | Economy | Positive |
| USA | Chrysler | Red | 1980 | Economy | Negative |
| Japan | Honda | White | 1980 | Economy | Positive |
| Japan | Toyota | Green | 1980 | Economy | Positive |
| Japan | Honda | Red | 1990 | Economy | Negative |
References
[Mitchell, 1997] Mitchell, T. (1997). Machine Learning. McGraw Hill, New York, USA.
