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Chapter 9 Data Analysis CS267 By Anand Sivaramakrishnan
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Chapter 9 Data Analysis CS267

Jan 07, 2016

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Chapter 9 Data Analysis CS267. By Anand Sivaramakrishnan. A Decision table is defined as follows T = (U,A,C,D) where U = universe A = set of actions C = condition attributes D = decision attributes C,D is subset of A. - PowerPoint PPT Presentation
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Page 1: Chapter 9 Data Analysis CS267

Chapter 9

Data AnalysisCS267

By Anand Sivaramakrishnan

Page 2: Chapter 9 Data Analysis CS267

A Decision table is defined as follows

T = (U,A,C,D)

where U = universe

A = set of actions

C = condition attributes

D = decision attributes

C,D is subset of A

Page 3: Chapter 9 Data Analysis CS267

Core is a condition attribute value which is indispensable that means it is that value that has direct impact on the value of decision attribute.

Reduct is a decision rule which must satisfy following conditions1. The rule must be true or consistent.2. Predecessor of rule must be independent.

Page 4: Chapter 9 Data Analysis CS267

To simplify the decision table

Removal of unnecessary or superfluous

Follow these steps.

1.Removing redundancy.

2.Checking functional dependency/ Removing superfluous attributes.

3.Categorizing the decisions into decision classes

4.Find core values of all decision rules.

5.Find the value reducts of each decision rule.

Page 5: Chapter 9 Data Analysis CS267

Table 1

Page 6: Chapter 9 Data Analysis CS267
Page 7: Chapter 9 Data Analysis CS267

After removing all the redundant decision rules we get table 2

Table 2

Page 8: Chapter 9 Data Analysis CS267

• After removing attribute ‘a’

Table 3

Page 9: Chapter 9 Data Analysis CS267

• Therefore attribute ‘a’ is indispensable.

Page 10: Chapter 9 Data Analysis CS267

Removing attribute ‘b’

Table 4

Page 11: Chapter 9 Data Analysis CS267

• This means that after removing attribute ‘b’ the table remains consistent.

• That means attribute ‘b’ is a superfluous attribute

• It is dispensable.

Page 12: Chapter 9 Data Analysis CS267

After removing attribute ‘c’ we get Table 5

Table 5

Page 13: Chapter 9 Data Analysis CS267

In table 5 the following 2 rules are in consistent

that means attribute ‘c’ is indispensable.

Page 14: Chapter 9 Data Analysis CS267

After removing attribute ‘d’ we get Table 6 Table 6

Page 15: Chapter 9 Data Analysis CS267

In table 6, the following rules make it inconsistent

therefore attribute ‘d’ is indispensable

Thus, (a,c,d) is the D-core and also the D-reduct of C.

Page 16: Chapter 9 Data Analysis CS267

Therefore, we remove only attribute ‘b’, after which we also remove redundancy that occurred because of the removal.

Table 7

Page 17: Chapter 9 Data Analysis CS267

• As there are similar decisions for different conditions, we can group similar decisions into decision classes.

(e2,f4) denoted as I

(e1,f4) denoted as II

(e2,f3) denoted as III

(e2,f2) denoted as IV

Page 18: Chapter 9 Data Analysis CS267

Table 8

Now we compute which attribute values are dispensable and which ones are indispensable with respect to each decision class.

Values ‘a’ and ‘d’ are indispensable due to the following set of rules.

Page 19: Chapter 9 Data Analysis CS267

Core Values Value Reduct

Page 20: Chapter 9 Data Analysis CS267

In the decision classes I and II sets of core values of each decision rule are also reducts

but the same does not apply for classes III and IV.

Page 21: Chapter 9 Data Analysis CS267

Value Reducts Table 10

Page 22: Chapter 9 Data Analysis CS267

References

• Chapter 9 Data Analysis

• Chapter 8 Slides – Gayatri and Bhargav

Page 23: Chapter 9 Data Analysis CS267

Thank YouQ&A