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CECS632
Data Mining
Tulay Muezzinoglu
Corrections to the textbook:
 Chapter 2):
1. Page 29: In the third sentence of the second paragraph the word “row” should be “raw”.
2. Page 35: In the Table 2.4 p value for the sample s7 is missing and should be equal to 2.
 Chapter 3):
3. Page 44: In the example, the value of Var(XB) was written and computed as 0.6333.That
value should be 0.06333, hence the result is 0.169967.
4. Consequently, |mean(XA)-mean(XB)| / SE(XA-XB) = 0.196116
5. Page 48: In the formula for entropy, the initial point for inner summation should be small
letter i.
 Chapter 5)
6. Page 100: The value of mean A is not correct. It should be 5.4 instead 0f 5. The rest of
the solution should be corrected according to this value, e.g. Beta is equal to 0.92.
7. Page 113: In question 3, “Figure 4.2” should be replaced by “Table 5.1”.
8. Page 114: In question 4.c “Figure 4.5” should be replaced by “Table 5.3”.
 Chapter 6)
9. Page 135: In the paragraph starting with “How is the output…” The sentence “Data that
we do not expect will contain clusters should not be processed by any clustering
algorithm” seems to have structural error.
 Chapter 7)
10. Page 147: Info(T1) should be calculated as -(2/5)log2(2/5)-(3/5) log2(3/5) = 0.97.
11. Consequently Gain(x4) = 0.97 - 0 = 0.97 bits.
12. Page 151: In the equation for InfoX1(T) the third factor should be 5/13 not 5/14.
InfoX1(T) = 5/13(…)+3/13(…)+5/13(…). The result is correct.
13. Page 151:Split-info(x1) should be calculated as
-(5/14)log2(5/14)-(3/14)log2(3/14) -(5/14)log2(5/14) -(1/14)log2(1/14) = 1.8
14. Page 154: In Figure 7.9 the node on the right should be CLASS1(16,1)
 Chapter 8)
15. Page 186: In the LRS set, ABE seems to be missing.
16. Page 192: The number label of the first question is incorrect. It should be 6th instead of
5th and the “6” should be deleted in the line starting with “using the threshold…”
17. Page 192: In question 8, the method (Apriori or FP) to be used in the solution is not
stated.
 Chapter 9)
18. Page 203: The equation for the adjustment of the weight is a special case where the
activation function of the output of the perceptron is linear.
19. Page 215: In the formula about the change in the weights, the notation used for weights is
not consisted with the example.
20. Page 217: In the calculations above the Figure 9.14, ’s should be deleted.
 Chapter 10)
21. Page 225, Line 6: ¡°x=3 is the correct solution of the problem that maximizes y¡±
Comment: x=1 seems to be the correct solution.
22. Page 232, Line 3: ¡°Clearly, the chromosome CR4 in our example is the best of the
four chromosomes¡±
Comment: CR2 is the best
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CECS632
Data Mining
Tulay Muezzinoglu
23. Page 242, Line 15: (x***r*)
Comment: It strangely changed from (x***s*) defined previously as C1 to (x***r*)
24. Page 244: In the 7th question S3 is invalid for the question.
25. Page 264: The table related to the resulting fuzzy set B’ is incorrectly labeled as B.
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