Determine probability that the patient has metastatic cancer

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Reference no: EM131076781

Homework 4

Q1 Bayesian Networks: Metastatic cancer is a possible cause of brain tumors and is also an explanation for increased total serum calcium. In turn, either of these could explain a patient falling into a coma. Severe headache is also associated with brain tumors. A BN representation of this metastatic cancer example is shown below (Figure 1). All the nodes are Booleans. Given that a patient has severe headache, has a brain tumor, not in coma and does not have symptoms of increased serum calcium, determine the probability that the patient has metastatic cancer.

1977_A BN representation of metastatic cancer .jpg

Q2 Given the following classification rule on weather data, prune it so that it is not an overfit. The goal is to obtain a good rule whose support is at least 3 and accuracy is 50% or more. The current rule has a support of 1 and accuracy of 100%. Show your work.

Outlook=sunny and temp=cool and humidity=normal and windy=false ==> Play = Yes

What to submit? Submit a pdf file with your answers via the Blackboard. Your output should look like this:

Name Course HW#

Q1 Work and results for Q1

Q2 Work and results for Q2

Homework 5

Q1. Given the following data, show ways to discretize age based on (i) Equal-width binning (4 bins) (ii) Equal frequency binning (4 bins) (iii) :
Entropy-based discretization. Salary is the outcome class.

Age

Experience

Education

Salary

45

20

MS

High

65

40

BS

Medium

25

5

HS

Low

35

10

BS

High

27

5

BS

High

22

0

BS

Low

'30

3

MS

Medium

66

40

MS

Medium

50

25

BS

Medium

37

15

BS

High

33

10

MS

Medium

40

15

MS

High

23

5

HS

Low

24

2

ES

Medium

Q2. Transform salary into binary variables using the standard method, the err-correcting code method, and nested dichotomies.

Reference no: EM131076781

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