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刊误（chapter 1 - chapter 5）

呆呢鹿夢遊中 对 Machine Learning 的书评 发表时间：2016-08-29 12:08:51

纯搬运。

来自：https://www.cs.ubc.ca/~murphyk/MLbook/errata.html

提交新的bug fix：https://docs.google.com/forms/d/e/1FAIpQLSdOXvmnvuIQn__t0xPyTErj53L-qo_RerImgKbXV4VfLDI6SQ/viewform?formkey=dEp2U2hRWXVpMU5nd05YcEJKVFNUdmc6MQ


- preface: added printing history to the end of the preface, to make it easier for the reader to determine which version they have

- sec 1.1: reworded description of the long tail


-p4 Added reference to Nate Silver book (‘The Signal and the Noise’) and reformatted sec 1.2.1.2

- footnote 3 on p31: 'risk reverse reward' should be 'risk versus reward'

- p35 After eqn 2.35: ref to “Figure 2.1(b-c)” should say “Figure 2.1”.

- sec 2.2.3 Added quote by Jeffreys’73 and ref to the book by Sharon McGrayne (2011) to the Bayes rule section

- sec 2.4.2 on student T distribution was missing subsection title; this change has
caused all subsequent subsections in 2.4 to be renumbered

- p.68: iff (if and only if) [and not "iff (***iff*** and only if)]

- equation 3.14 (p.74). should be
     ***p(theta | D)*** equiv. p(D | theta) * p(theta) = (...)

- p.74, 2nd parag.: missing ')' after first theta in p(D |
theta***)*** equiv. P(s(D) | theta)

- p.74, end of 1st line in section 3.3.2: missing 'be' in "it would
***be*** convenient (...)"

- p.74, penultimate parag.: "and that we think it lives in the
interval (0.05, 0.30) with
          probability ***???***, then ..." [is a value missing there???]

- Page 84, line 8 of Algorithm 3.1. for theta_jc, you should have N_c, not N.

- page 85, equation 3.67, the subindex k should be c.
 
- eqn 3.90 (in exercise 3.3) typo: should be Gamma(a0+a1+1) = (a0+a1) Gamma(a0+a1)

- eqn 3.93 (exercise 3.9) should be max(D, b) instead of max(D)

- eqn 4.62 Should be delta_c = x’ beta_c + gamma_c

- eqn 4.82 Should be vmu_{1|2} = -vL_1^{-1} vL_2 vx_2

- eqn 4.181 Should be SN = SO + Smu, not inv(SN)

- eqn 4.197 Should be exp(-1/2 tr(Sigma(-1) S)) not exp(-N/2 …)

- sec 4.5 Distribution of scatter matrix is S ~ Wi(Sigma, N) not Wi(Sigma, 1)

 - ex 4.8c. Whitening uses U and Lambda, which are the eigenvectors /
 values of X'X, not X

- sec 5.7.2.1 Added footnote that AUC is equivalent to a pairwise ranking criterion







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书名： Machine Learning
作者： Kevin P·Murphy
出版社： The MIT Press
副标题： A Probabilistic Perspective
出版年： 2012-8-24
页数： 1104
定价： USD 90.00
装帧： Hardcover
ISBN： 9780262018029