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LDAのハイパーパラメータの性質

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第1回 Machine Learning 15minutes! の登壇資料です。
http://machine-learning15minutes.connpass.com/event/32889/

LDAの基本的な説明と、ハイパーパラメータの振る舞いを少し確認しています。
スライドには書き忘れましたが、計算はすべてgensimで行っています。
ハイパーパラメータの最適化も関数の引数に与えるだけでできてしまいます。

Published in: Data & Analytics
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LDAのハイパーパラメータの性質

  1. 1. 1
  2. 2. • • • • • • 2
  3. 3. • • • • • 2 • • • • • 3
  4. 4. 4
  5. 5. • 1988 LSI • car automobile • • bag of words ! • 1998 PLSI • 2003 LDA • LDA 2016 • python gensim • LDA 5
  6. 6. LDA • • • • A a a B C B a C a
  7. 7. LDA http://www.ism.ac.jp/~daichi/lectures/H24-TopicModel/ISM-2012-TopicModels-daichi.pdf LDA
  8. 8. LDA w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169
  9. 9. LDA w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ a b c c c c c b d b b b a d b a a
  10. 10. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ LDA a b c c c c c b d b b b a d b a a
  11. 11. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 A LDA a b c c c c c b d b b b a d b a a
  12. 12. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 2 A LDA a b c c c c c b d b b b a d b a a
  13. 13. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 3 A LDA a b c c c c c b d b b b a d b a a
  14. 14. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 C LDA a b c c c c c b d b b b a d b a a
  15. 15. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ A a LDA a b c c c c c b d b b b a d b a a
  16. 16. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ B a LDA a b c c c c c b d b b b a d b a a
  17. 17. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ C a LDA a b c c c c c b d b b b a d b a a
  18. 18. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ θ φ 1 1 1 1 LDA a b c c c c c b d b b b a d b a a
  19. 19. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 A 1 1 LDA a b c c c c c b d b b b a d b a a
  20. 20. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 2 LDA a b c c c c c b d b b b a d b a a
  21. 21. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 2 a LDA a b c c c c c b d b b b a d b a a
  22. 22. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 a b c c c c c LDA a b d b b b a d b a a
  23. 23. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 1 a b c c c c c LDA a b d b b b a d b a a
  24. 24. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 a b c c c c c LDA a b d b b b a d b a a
  25. 25. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 2 a b c c c c c b d b b b LDA a d b a a
  26. 26. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 2 a b c c c c c b d b b b LDA a d b a a
  27. 27. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 3 a b c c c c c b d b b b a d b a a LDA
  28. 28. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 3 a b c c c c c b d b b b a d b a a LDA
  29. 29. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ φ a b c c c c c b d b b b a d b a a LDALDA
  30. 30. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ a b c c c c c b d b b b a d b a a LDA
  31. 31. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 1 1 a b c c c c c b d b b b a d b a a LDA
  32. 32. w α β θ φ z http://www.slideshare.net/MasayukiIsobe/ss-35851169 φ θ 1 1 1 a b c c c c c b d b b b a d b a a LDA
  33. 33. • • • 33
  34. 34. 34 α=(1, 1, 1) alpha=1,1,1 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=1,1,1 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=1,1,1 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000
  35. 35. 35 α=(0.1, 0.1, 0.1) alpha=01,01,01 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=01,01,01 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=01,01,01 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000
  36. 36. 36 α=(0.1, 0.2, 0.3) alpha=01,02,03 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=01,02,03 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=01,02,03 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000
  37. 37. 37 α=(0.1, 0.2, 0.3) alpha=01,02,03 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=01,02,03 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000 alpha=01,02,03 value Frequency 0.0 0.2 0.4 0.6 0.8 1.0 010000200003000040000500006000070000
  38. 38. 38 1. α=1/ 2. α 150
  39. 39. 39 http://news.livedoor.com/article/detail/5903225/2011-10-02T10:00:00+0900 TV TV 1 http://news.livedoor.com/topics/detail/5899457/ 200 !? http://news.livedoor.com/topics/detail/5801160/ TATSUYAKAWAGOE 9,000 TV 6 TV 2 “ ” 1 http://news.livedoor.com/topics/detail/5655259/ 15 http:// news.livedoor.com/topics/detail/5865240/ …… http://news.livedoor.com/topics/detail/5558182/ TV …… http://news.livedoor.com/topics/detail/5858898/ “ ” / http://news.livedoor.com/topics/detail/5828874/ http://news.livedoor.com/topics/detail/5759728/ http://news.livedoor.com/topics/detail/5801859/ http://news.livedoor.com/topics/detail/5571502/ 770
  40. 40. 1.α= 40 (0, '0.013* + 0.011*: + 0.010*- + 0.010*livedoor + 0.009* + 0.008* + 0.008* + 0.008*. + 0.007* + 0.007* ') (1, '0.010* + 0.010*: + 0.007*- + 0.007* + 0.007* + 0.007*. + 0.007* + 0.006* + 0.006* + 0.006* ') (2, '0.015*. + 0.011*- + 0.011* + 0.010*: + 0.008* + 0.007*livedoor + 0.007*http + 0.007* + 0.007* + 0.007* ') (3, '0.014*- + 0.013*. + 0.013* + 0.012*livedoor + 0.009*: + 0.009* + 0.009* + 0.008* + 0.008* + 0.007* ') (4, '0.016*. + 0.015*- + 0.014*: + 0.013* + 0.012* + 0.010* + 0.008*livedoor + 0.007* + 0.007*:// + 0.007*http') (5, '0.009*. + 0.008*: + 0.007*- + 0.007* + 0.007* + 0.007*" + 0.006* + 0.006* + 0.006* + 0.006* ') (6, '0.010*. + 0.008* + 0.008* + 0.007*: + 0.006* + 0.006*com + 0.006*- + 0.005*article + 0.005*livedoor + 0.005*NHK') (7, '0.015* + 0.013*- + 0.012* + 0.011*. + 0.010* + 0.010*: + 0.009* + 0.007* + 0.006* + 0.006* ') (8, '0.015*. + 0.011*- + 0.010* + 0.009* + 0.008*: + 0.008* + 0.008*livedoor + 0.007* + 0.007* + 0.007* ') (9, '0.015*. + 0.013*- + 0.012*: + 0.010* + 0.009*livedoor + 0.008* + 0.008* + 0.007* + 0.007* + 0.006*news') (10, '0.016* + 0.011* + 0.008* + 0.008*: + 0.008* + 0.007*. + 0.006* + 0.006*" + 0.006* + 0.006*-')
  41. 41. 2.α= 41 (0, '0.012* + 0.009* + 0.009* + 0.009* + 0.009* + 0.009* + 0.008* + 0.008* + 0.008* + 0.008* ') (1, '0.015*: + 0.013* + 0.011* + 0.011*- + 0.010*. + 0.008* + 0.007* + 0.007*livedoor + 0.007* + 0.006* ') (2, '0.010* + 0.010*. + 0.008*: + 0.006* + 0.006* + 0.006*- + 0.006* + 0.006* + 0.006*livedoor + 0.005* ') (3, '0.024*. + 0.014*- + 0.010*: + 0.009* + 0.009* + 0.007*http + 0.007*com + 0.007*article + 0.007*detail + 0.006*T') (4, '0.013* + 0.012* + 0.011*- + 0.010*. + 0.010*e + 0.009*: + 0.008* + 0.008* + 0.008* + 0.007* ') (5, '0.015* + 0.011*- + 0.010*. + 0.008*: + 0.007* + 0.007* + 0.006* + 0.006* + 0.006* + 0.006* ') (6, '0.010*. + 0.010*- + 0.009*: + 0.009* + 0.007* + 0.006*livedoor + 0.006* + 0.006* + 0.005* + 0.005*T') (7, '0.017*. + 0.013*- + 0.013* + 0.010*livedoor + 0.010* + 0.009*: + 0.009*:// + 0.008*com + 0.008* + 0.007* ') (8, '0.013* + 0.011*. + 0.009* + 0.009* + 0.008*: + 0.008*AD + 0.008* + 0.007*- + 0.007* + 0.007*TBS') (9, '0.016*. + 0.009* + 0.007* + 0.006*: + 0.006* + 0.006*detail + 0.006* + 0.006*- + 0.006*news + 0.006* ') (10, '0.013* + 0.013*. + 0.012*- + 0.011*: + 0.010* + 0.009*livedoor + 0.008* + 0.008* + 0.007* + 0.007* ') URL
  42. 42. 2.α= URL 42 (53, '0.031*. + 0.013*- + 0.013*: + 0.013*:// + 0.012*livedoor + 0.011*news + 0.011*http + 0.011*com + 0.010*detail + 0.009*article') α the
  43. 43. • • • • • 43

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