Problem Description
Implement (in C++) 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 additional training examples required to exactly learn the target concept:
< Sunny, W arm, ?, ?, ?, ?
In a ZIP file, place the source code, executable, and a text file containing your list of random training examples and the answer to Q1. Upload ZIP file to Vula before 10.00 AM, 19 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
1
References
[Mitchell, 1997] Mitchell, T. (1997). Machine Learning. McGraw Hill, New York, USA.
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