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Name OverallGrade Obedient ResearchScore ProjectScore Recommend Henry A Y 90 85 Yes John C N 85 51 Yes David F N 10 17 No Holmes
Name | OverallGrade | Obedient | ResearchScore | ProjectScore | Recommend |
Henry | A | Y | 90 | 85 | Yes |
John | C | N | 85 | 51 | Yes |
David | F | N | 10 | 17 | No |
Holmes | B | Y | 75 | 71 | No |
Marvin | E | N | 20 | 30 | No |
Simon | A | Y | 92 | 79 | Yes |
Robert | B | Y | 60 | 59 | No |
Trent | C | Y | 75 | 33 | No |
Task1: Use Python to create a table with the average, medium, min, max and standard deviation for each attributes in the dataset.
Task2: Use Python to plot a histogram for each attributes in the dataset.
Task3: Compute the correlation table for the quantitative attributes.
Task4: Build a decision tree to the above dataset using all the relevant predictors. Find the model by using the following method:
- An entropy measure (pen and paper)
- Pyhton code.
- Task5: Use the created Mode in Task 4 to Predict the class of the following new examples:
Name OverallGrade Obedient ResearchScore ProjectScore 0 Nathan F N 30 20 1 Thomas A Y 78 80
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