Lab 2: Concept Learning Solution

Problem Description




Implement (in C++ only) the FIND-S algorithm ( chapter 2 [Mitchell, 1997]). Use the training examples in table 1 to verify that it successfully produces the trace described in section 2.4 [Mitchell, 1997] for the Enjoysport example.




Q1: Now use this program to determine the number of random training examples required to exactly learn the target concept:




< Sunny; W arm; ?; ?; ?; ?




In a ZIP le, place the source code, executable, and a text le containing your list of random training examples and the answer to Q1. Upload ZIP le to Vula before 10 AM, 10 August.







Table 1: Positive and negative training examples for target concept EnjoySport




Example
Sky
AirTemp
Humidity
Wind
Water
Forecast
EnjoySport
















1
Sunny
Warm
Normal
Strong
Warm
Same
Yes
















2
Sunny
Warm
High
Strong
Warm
Same
Yes
















3
Rainy
Cold
High
Strong
Warm
Change
No
















4
Sunny
Warm
High
Strong
Cool
Change
Yes





















References




[Mitchell, 1997] Mitchell, T. (1997). Machine Learning. McGraw Hill, New York, USA.