Errata for First Edition
This page contains the errata for the first edition. You can contact us via email if you want to report any errors.
Chapter 1: Data Mining and Analysis
p4, Section 1.3, line 13: as linear combination **should be** as a linear combination
p9, Example 1.3, 3rd line from end: (153)1/3 should be (152)1/3
p9, Example 1.3, last line: (43+(−1)3)1/3=(63)1/3=3.98 should be (43+∣−1∣3)1/3=(65)1/3=4.02
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p24, Section 1.4.3, last line of subsection Univariate Sample:
where fX is the probability mass or density function for X
should be
where fX is the probability mass or density function for X
p30, Section 1.7, Q1: in (1.5) should be in Eq. (1.5)
Chapter 2: Numeric Attributes
p34, Equation (2.2): ˆF(x)≥q should be F(x)≥q
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p34, Line after Equation (2.2):
That is, the inverse CDF gives the least value of X, for which q fraction of the values are higher, and 1−q fraction of the values are lower.
should be
That is, the inverse CDF gives the least value of X, for which q fraction of the values are '''lower''', and 1−q fraction of the values are '''higher'''.
p53, Example 2.6, line 1: ... range for Income is 2700−300=2400 should be ... range for Income is 6000−300=5700
p55, In Eq (2.32): P(−k≤z≤k)=P(0≤t≤k/√2) should be P(−k≤z≤k)=2⋅P(0≤t≤k/√2)
p58, Total and Generalized Variance, Line 2: ...product of its eigenvectors should be ...product of its eigenvalues
p58, two lines above Example 2.8: tr(Λ) should be tr(Λ)
p61, Q3: mu should be μ so that it reads
Chapter 3: Categorical Attributes
p81, Table 3.6, Attribute value for X2: Short(a23) should be Long(a23)
Chapter 4: Graph Data
p103, 2 lines above Eq (4.3): γjk=0 should be γjk(vi)=0
p103, Eq (4.3): γjk should be γjk(vi)
p103, Example 4.5, last line: γjk>0 should be γjk(v5)>0
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p104, Example 4.5:
c(v5)=γ18+γ24+γ27+γ28+γ38+γ46+γ48+γ67+γ68
should be
c(v5)=γ18(v5)+γ24(v5)+γ27(v5)+γ28(v5)+γ38(v5)+γ46(v5)+γ48(v5)+γ67(v5)+γ68(v5)
p107: p1=12(11212) should be p1=12(12212)
p127, 4th Line after Eq (4.22): initial n0 edges should be initial n0 nodes
Chapter 5: Kernel Methods
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p138, Example 5.4:
μϕ=∑5i=1ϕ(xi)=∑5i=1xi
should be
μϕ=15∑5i=1ϕ(xi)=15∑5i=1xi
p140, 7th Line after Eq (5.3): Unexpected text node: ' ' should be Unexpected text node: ' '
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p141, 3rd line and 10th Line before Sec 5.1.2: There is an extra left bracket in definition of ϕ(x), that is,
((K(x1,x),... should be (K(x1,x),...
p144, 2nd line: ∫a(x)2dx<0 should be ∫a(x)2dx<∞
p144, last line: ∑qk=1 should be ∑qk=0
p156, Section 5.4.2: all occurrences of path/paths should be walk/walks
p160, Example 5.15L S=−L=A−D should be S=−L=A−Δ
Chapter 6: High-dimensional Data
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p164: In the definitions of the hyperball and and hypersphere
x=(x1,x2,…,xd) should be x=(x1,x2,…,xd)T
p171: 0d=(01,02,…,0d) should be 0d=(01,02,…,0d)T
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p172, Section 6.6, 1st Line after Eq. (6.11):
μ in equation μ=0d should be in bold.
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p178, section Volume in d dimensions:
x1=rcosθ1cosθ2cosθ3=rc2c2c3 should be x1=rcosθ1cosθ2cosθ3=rc1c2c3
x3=rcosθ1sinθ2=rc1s1 should be x3=rcosθ1sinθ2=rc1s2
p178, Equation for J(θ1,θ2,θ3), Entry in first row, fourth column: rc1c2s3‘∗∗shouldbe∗∗:math:-r c_1 c_2 s_3`
p207, line 3, Alg 7.2: η1,η2,...,ηd should be η1,η2,...,ηn
Chapter 7: Dimensionality Reduction
p186, line 1: ar is vector should be ar is a vector
p207, line 3, Alg 7.2: η1,η2,...,ηd should be η1,η2,...,ηn
Chapter 8: Itemset Mining
p235, Example 8.13, 2nd last line: ...,AB(3),AD(4),... should be ...,AB(4),AD(3),...
p236, 5th line: ...,AD(4),... should be ...,AD(3),...
Chapter 9: Summarizing Itemsets
p250, 2nd line under '''Generalized Itemsets''': k-tidsets should be k tidsets
p250, 4th line from bottom: Z=Y∖X should be Z=X∖Y
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p252, Eq. (9.3) and Eq. (9.4): ∣X∖Y∣ should be ∣X∖W∣ on the right hand side in both equations, so that they read
Upper Bounds(∣X∖Y∣is odd):sup(X)≤∑Y⊆W⊂X−1(∣X∖W∣+1)sup(W)
Lower Bounds(∣X∖Y∣is even):sup(X)≥∑Y⊆W⊂X−1(∣X∖W∣+1)sup(W)
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p254, Section '''Nonderivable Itemsets''', 1st Equation after line 1: ∣X∖Y∣ should be ∣X∖W∣ , so that it reads
IE(Y)=∑Y⊆W⊂X−1(∣X∖W∣+1)⋅sup(W)
Chapter 10: Sequence Mining
p264, alg 10.2, line 9: P should be Pa
Chapter 11: Graph Pattern Mining
p288, sec 11.3, 2nd paragraph, line 6: sup(C)=sup(t) should be sup(C′)=sup(t)
p290, Figure 11.8: The last tuple in the DFS-code for graph C19 should be ⟨2,0,a,a⟩ and not ⟨2,0,a,b⟩
p292, Algorithm 11.2, Line 14: b=⟨ur,v,L(ur),L(v),L(ur,v)⟩ should be b=⟨ur,v,L(ϕ(ur)),L(ϕ(v)),L(ϕ(ur),ϕ(v))⟩
p293, Figure 11.9 (c): There there should be one more extension for ϕ5, namely ⟨0,3,a,b⟩
p294, Algorithm 11.3, Line 12: NGj should be NG
p295, Algorithm 11.4, Line 0: C should be C={t1,t2,...,tk}
Chapter 12: Pattern and Rule Assessment
p322 (Alg 12.1) and p326 (Alg 12.2): replace = with ←
Chapter 13: Representative-based Clustering
p343, in 3rd equation: P(Ci) should be P(C1)
p335, Algorithm 13.1, line 7: μti should be μt−1i
Chapter 14: Hierarchical Clustering
p366, Fig 14.2: (a) m=1, (b) m=2, and (c) m=3 should be (a) n=1, (b) n=2, and (c) n=3, respectively.
p373, sec 14.4: EXERCISES AND PROJECTS should be EXERCISES
p373, Q1, SMC(Xi,Xj), JC(Xi,Xj), RC(Xi,Xj) should be SMC(xi,xj), JC(xi,xj), RC(xi,xj), respectively.
Chapter 15: Density-based Clustering
p385, line after Eq. (15.6): ... having two parts. A vector ... should be ... having two parts: a vector ...
p387, Alg 15.2, line 20: In the numerator K(xt−xih)⋅xt should be K(xt−xih)⋅xi
Chapter 16: Spectral and Graph Clustering
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p411, 2nd last equation: 12prs should be prs so that it reads
prs=dr2mds2m=drds4m2
p413, Line 5: ∑nj=1dTci should be dTci
p413, Line 10: (dTici)2 should be (dTci)2
p424, Q5: cn=1√n1 should be cn=1√∑ni=1diΔ1/21
p424, Q6 (b): K=M should be K=M+I
Chaper 17: Clustering Validation
p428, Example 17.1, Table below 2nd para: n=100 should be n=150 for the total count
p463, Q10: Add the sentence Assume that the clusters are: C1={a,b,c,d,e},C2={g,i},C3={f,h,j},C4={k}.
Chapter 18: Probabilistic Classification
p472, Table 18.2: 13/50 should be 11/50
p472, Example 18.2, 2nd Para, lines 6 and 7: P(c1∣x) and P(c2∣x) should be ˆP(c1∣x) and ˆP(c2∣x), respectively.
Chapter 20: Linear Discriminant Analysis
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p503: Example 20.2: There should be no transpose operator T on the mean vectors, i.e.,
μ1=(5.013.42)Tμ2=(6.262.87)Tμ1−μ2=(−1.2560.546)T
should be
μ1=(5.013.42)μ2=(6.262.87)μ1−μ2=(−1.2560.546)
p509, Example 20.4, line 4: ''iris-virginica'' should be Iris-versicolor
p512, Q1: In part (a) SB should be B, and in (b) SW should be S
Chapter 21: Support Vector Machines
p526, 7th line, in Ldual: (C−αi+βi) should be (C−αi−βi)
p536, Algorithm 21.1, line 15: αt+1=α should be αt+1←α
p538, Example 21.8, line 5: homogeneous quadratic kernel K(xi,xj)=(xTixj)2 should be inhomogeneous quadratic kernel K(xi,xj)=(1+xTixj)2