#JJUG - Java でカジュアルにはじめる機械学習

JJUG ナイト・セミナー「機械学習・自然言語処理特集！」12/17（水）での発表資料です。

セミナー概要はこちら:
http://jjug.doorkeeper.jp/events/18378

Transcript

1. Java ͰΧδϡΞϧʹ͸͡ΊΔ
   ػցֶश
   2014-12-17 JJUG night seminar
   @komiya_atsushi
   

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2. ͓·ͩΕ
   

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3. ,0.*:""UTVTIJ
   !LPNJZB@BUTVTIJ
   

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6. "EUFDI
   +BWBFOHJOFFS
   

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7. ࠓ೔ͷτϐοΫ
   

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8. ػցֶशʂ ػցֶशʂ
   • ػցֶशͷಋೖతͳ࿩ͱɺJava ͰΧδϡΞϧʹػ
   ցֶश͢Δ࿩͕ϝΠϯͱͳΓ·͢
   • Ψνͷํ͸৸͍ͯͯͩͬͯ͘͞ߏ͍·ͤΜ
   • େن໛σʔλʹର͢Δػցֶशͷ͓࿩͸

   Ԑా͞Μʹ͓೚ͤ͠·͢ʂ
   • ࣗવݴޠॲཧʹ͍ͭͯ͸͡ΐʔͨʹ͞Μʹ

   ͓೚ͤ͠·͢ʂ
   

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9. ػցֶशΛ͸͡ΊΔલʹ
   ஌͓͖͍ͬͯͨ͜ͱ
   

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10. ػցֶशͱ͸ͳΜͧ΍ʁ
    ػցֶशνϡʔτϦΞϧˏ+VCBUVT$BTVBM5BMLT
    http://www.slideshare.net/unnonouno/jubatus-­‐casual-­‐talksΑΓҾ༻͠·ͨ͠ɻ
    

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11. ػցֶशͰԿ͕Ͱ͖Δͷ͔
    ෼ྨɾࣝผ
    ༧ଌɾճؼ
    ύλʔϯϚΠχϯά
    ΞιγΤʔγϣϯϧʔϧ
    ΫϥελϦϯά
    εύϜϝʔϧͷݕ஌
    χϡʔεهࣄͷΧςΰϦ෼ྨ ঎඼Ϩίϝϯσʔγϣϯ
    धཁɾച্༧ଌ
    ʜͳͲͳͲ
    

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12. ػցֶशͰԿ͕Ͱ͖Δͷ͔
    ύλʔϯϚΠχϯά
    ΞιγΤʔγϣϯϧʔϧ
    ΫϥελϦϯά
    εύϜϝʔϧͷݕ஌
    χϡʔεهࣄͷΧςΰϦ෼ྨ ঎඼Ϩίϝϯσʔγϣϯ
    धཁɾച্༧ଌ
    ڭࢣ͋Γֶश
    ɾਖ਼ղ͕͋Δ
    ɾʮϞσϧʯΛ࡞Δ
    ෼ྨɾࣝผ
    ༧ଌɾճؼ
    

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13. ػցֶशͰԿ͕Ͱ͖Δͷ͔
    ࣝผɾ෼ྨ
    ճؼɾ༧ଌ
    ύλʔϯϚΠχϯά
    ΞιγΤʔγϣϯϧʔϧ
    ΫϥελϦϯά
    εύϜϝʔϧͷݕ஌
    χϡʔεهࣄͷΧςΰϦ෼ྨ ঎඼Ϩίϝϯσʔγϣϯ
    धཁɾച্༧ଌ
    ڭࢣͳֶ͠श
    

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14. • ͲΜͳܗࣜͷσʔλͰ΋ OK ͱ͍͏Θ͚Ͱ͸ͳ͍
    • ݪଇͱͯ͠਺஋ྻʢϕΫτϧʣ͔͠ѻ͑ͳ͍
    • ඇߏ଄σʔλʢը૾ɺԻ੠ɺςΩετɺΞΫηεϩάɺetc.ʣ͸ͦͷ·
    ·Ͱ͸ѻ͑ͳ͍
    • ඇߏ଄σʔλ͔Β͞·͟·ͳʮಛ௃ྔʯΛநग़ͯ͠ʮಛ௃ϕΫτϧʯΛ
    ࡞Δ
    • ΧςΰϦΧϧม਺͸μϛʔม਺Ͱදݱ͢Δ
    • εέʔϦϯά
    • feature engineering
    • ڭࢣ͋Γֶशͷ܇࿅σʔλͷ৔߹͸ɺՃ͑ͯʮϥϕϧʯͳͲਖ਼ղ৘ใΛ
    ෇༩͢Δ
    ԿΛೖྗσʔλͱ͢Δͷ͔
    

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15. ಘΒΕͨ݁Ռ͸ਖ਼͍͠ͷ͔
    • ਖ਼͠͞Λ͔֬ΊΔ
    • k-෼ׂަࠩݕূ (k-fold cross validation)
    • ਖ਼͠͞ΛଌΔ
    • ෼ྨɾࣝผ
    • Precision, Recall, AUC, F-measure
    • ༧ଌɾճؼ
    • ૬ؔ܎਺ɺܾఆ܎਺ɺMAE, RMSE
    

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16. ઢܗ෼཭ɾඇઢܗ
    • Ұຊͷઢʢ௒ฏ໘ʣͰ఺ʢಛ௃ϕΫτϧʣΛ෼཭Ͱ͖Δ͔ʁ
    ઢܗ෼཭Մೳ ઢܗ෼཭ෆՄೳ ඇઢܗ
    
    

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17. ΦϯϥΠϯֶशɾΦϑϥΠϯֶश
    • ΦϯϥΠϯֶश
    • ஞ࣍ಘΒΕΔσʔλΛ΋ͱʹɺϞσϧΛਵ࣌ߋ৽͢Δ
    • ετϦʔϜॲཧతͳΠϝʔδ
    • ར༻ͨ͠σʔλ͸஝ੵ͢Δ͜ͱͳ͘ഁغͰ͖Δ
    • ʢઍ੾ͬͯ͸౤͛ɺઍ੾ͬͯ͸౤͛…ʣ
    • ΦϑϥΠϯֶश
    • ஝ੵ͞ΕͨσʔλΛ΋ͱʹɺϞσϧΛҰؾʹߋ৽͢Δ
    • όονॲཧʹ૬౰͢Δ
    

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18. Java Ͱػցֶश͢Δ
    

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19. ࠷ॳʹ͜Ε͚ͩ͸
    ݴ͓͖͍ͬͯͨ
    

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20. ंྠͷ࠶ൃ໌͸΍ΊΑ͏
    

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21. طଘͷϥΠϒϥϦ౳Λ
    ׆༻͠Α͏
    

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22. ػցֶशͷ࣮૷ɺਏΈ͔͠ͳ͍
    • ػցֶशΞϧΰϦζϜͷςετɺͱʹ͔͘ਏ͍
    • ʮςετॻ͔ͳ͍ͱ͔͓લ̋̋ͷલͰ΋ಉ͜͡ͱ
    ݴ͑Μͷʁʯ
    • ࣌ؒɾۭؒޮ཰ͷΑ͍࣮૷͸໘౗ɾ೉͍͠
    • the state of the art ͳΞϧΰϦζϜΛ࣮૷͢Δͷ΋ɺ
    େ෯ͳਫ਼౓޲্͕ݟࠐΊΔ৔߹ʹཹΊ͍ͨ
    • طଘϥΠϒϥϦ౳Λ࢖͏͚ͩͰ͸Ͳ͏ͯ͠΋ղܾͰ
    ͖ͳ͍৔߹ʹͷΈɺࣗલ࣮૷͢ΔΑ͏ʹ͍ͨ͠
    

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23. Java ʹΑΔػցֶश
    ޲͖ෆ޲͖
    

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24. ྫ͑͹͜ΜͳϫʔΫϑϩʔ
    1. ର৅ͱ͢Δ໰୊Λೝࣝ͢Δ
    • ͲͷΑ͏ͳλεΫ͕߹͏ͷ͔ʁ
    2. อ༗͍ͯ͠Δσʔλʹ͍ͭͯཧղΛਂΊΔ
    • ͲͷΑ͏ͳಛ௃ྔ͕நग़Ͱ͖Δͷ͔ʁ
    3. ϞσϧΛ࡞੒͢Δ
    • ͲͷΞϧΰϦζϜΛར༻͢΂͖͔ʁ
    • Ͳͷಛ௃ྔΛར༻͢΂͖͔ʁ
    4. ࡞੒ͨ͠ϞσϧΛධՁ͢Δ
    • ਫ਼౓͸͍͔΄Ͳ͔ʁ
    5. γεςϜʹ૊ΈࠐΉɾγεςϜԽ͢Δ
    

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25. ྫ͑͹͜ΜͳϫʔΫϑϩʔ
    1. ର৅ͱ͢Δ໰୊Λೝࣝ͢Δ
    • ͲͷΑ͏ͳλεΫ͕߹͏ͷ͔ʁ
    2. อ༗͍ͯ͠Δσʔλʹ͍ͭͯཧղΛਂΊΔ
    • ͲͷΑ͏ͳಛ௃ྔ͕நग़Ͱ͖Δͷ͔ʁ
    3. ϞσϧΛ࡞੒͢Δ
    • ͲͷΞϧΰϦζϜΛར༻͢΂͖͔ʁ
    • Ͳͷಛ௃ྔΛར༻͢΂͖͔ʁ
    4. ࡞੒ͨ͠ϞσϧΛධՁ͢Δ
    • ਫ਼౓͸͍͔΄Ͳ͔ʁ
    5. γεςϜʹ૊ΈࠐΉɾγεςϜԽ͢Δ
    ͜ͷ͋ͨΓͰ
    ػցֶशΛ
    ׆༻͢Δ
    

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26. ྫ͑͹͜ΜͳϫʔΫϑϩʔ
    1. ର৅ͱ͢Δ໰୊Λೝࣝ͢Δ
    • ͲͷΑ͏ͳλεΫ͕߹͏ͷ͔ʁ
    2. อ༗͍ͯ͠Δσʔλʹ͍ͭͯཧղΛਂΊΔ
    • ͲͷΑ͏ͳಛ௃ྔ͕நग़Ͱ͖Δͷ͔ʁ
    3. ϞσϧΛ࡞੒͢Δ
    • ͲͷΞϧΰϦζϜΛར༻͢΂͖͔ʁ
    • Ͳͷಛ௃ྔΛར༻͢΂͖͔ʁ
    4. ࡞੒ͨ͠ϞσϧΛධՁ͢Δ
    • ਫ਼౓͸͍͔΄Ͳ͔ʁ
    5. γεςϜʹ૊ΈࠐΉɾγεςϜԽ͢Δ
    ͜ͷ͋ͨΓ͸
    ΞυϗοΫͳ
    ෼ੳ͕ඞཁ
    

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27. ྫ͑͹͜ΜͳϫʔΫϑϩʔ
    1. ର৅ͱ͢Δ໰୊Λೝࣝ͢Δ
    • ͲͷΑ͏ͳλεΫ͕߹͏ͷ͔ʁ
    2. อ༗͍ͯ͠Δσʔλʹ͍ͭͯཧղΛਂΊΔ
    • ͲͷΑ͏ͳಛ௃ྔ͕நग़Ͱ͖Δͷ͔ʁ
    3. ϞσϧΛ࡞੒͢Δ
    • ͲͷΞϧΰϦζϜΛར༻͢΂͖͔ʁ
    • Ͳͷಛ௃ྔΛར༻͢΂͖͔ʁ
    4. ࡞੒ͨ͠ϞσϧΛධՁ͢Δ
    • ਫ਼౓͸͍͔΄Ͳ͔ʁ
    5. γεςϜʹ૊ΈࠐΉɾγεςϜԽ͢Δ
    +BWBʹ޲͍ͯ
    ͍Δͷ͸
    ͜ͷ͋ͨΓ
    

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28. దࡐదॴͰ͍͜͏
    • Java ͰػցֶशΛ༻͍ͨΞυϗοΫ෼ੳ͕Ͱ͖ͳ͍Θ͚Ͱ͸ͳ͍͕ɺR
    ͳͲΛ࢖͏ํ͕Ұൠతʢʁʣ
    • ෼ੳΛ͢ΔͨΊʹಛԽͨ͠؀ڥ͕޲͍͍ͯΔ
    • Java ͩͱ Weka ͱ͔ Spark ͷΠϯλϥΫςΟϒͳίϯιʔϧͱ͔
    • Java Ͱૉ௚ʹίʔυΛॻ͍ͯϏϧυͯ͠ɺ࠷ॳ͔Β࣮ߦ… Έ͍ͨͳ
    ͷ͸खֻ͕͔ؒΓա͗Δ
    • ҰํͰ R ͸ R ͰɺγεςϜԽʹ͸޲͔ͳ͍
    • HTTP ϦΫΤετΛड͚ͯɺαʔό಺ͰϦΞϧλΠϜͰػցֶशͨ͠
    ͍… Έ͍ͨͳγεςϜΛ࡞Γ͍ͨ৔߹ͳͲ
    

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29. Java ͔Β࢖͑Δ
    ػցֶशϥΠϒϥϦͳͲ
    

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30. liblinear-java
    • gradle ‘de.bwaldvogel:liblinear:1.95'
    • https://github.com/bwaldvogel/liblinear-java
    • ˒ 121
    • LibSVM Λઢܗ෼ྨɾճؼʹಛԽͨ͠΋ͷɺͷ Java ϙʔ
    ςΟϯά
    • ϥΠϒϥϦ
    • ΘΓͱؤுͬͯɺຊମ (C++ ൛) ͷ࠷৽όʔδϣϯʹ௥ै
    ͠Α͏ͱ͍ͯ͠Δ
    

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31. Weka
    • gradle ‘nz.ac.waikato.cms.weka:weka-stable:
    3.6.11'
    • ଟछଟ༷ͳػցֶशΞϧΰϦζϜ͕ఏڙ͞Ε
    ͍ͯΔ෼ੳϓϥοτϑΥʔϜ
    • ϥΠϒϥϦͱͯ͠΋ར༻͢Δ͜ͱ͕Ͱ͖Δ
    • ͱΓ͋͑ͣػցֶशΛ͸͡ΊͯΈΔͳΒɺ

    ·ͣ͸͜Ε͔Β
    

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32. MLlib (Spark)
    • gradle ‘org.apache.spark:spark-mllib_2.10:1.1.1'
    • https://github.com/apache/spark
    • ˒ 2,336
    • ෼ࢄॲཧϑϨʔϜϫʔΫ Spark ্Ͱͷར༻Λલఏͱͨ͠
    ϥΠϒϥϦ
    • ػೳ௥Ճɾվળ͕ࠓͩ੝Μ
    • ΞυϗοΫ෼ੳͷ؀ڥͱͯ͠΋ར༻Ͱ͖Δʢ͸ͣʣ
    • ৄ͍͠࿩͸͜ͷޙͷԐా͞ΜτʔΫʹظ଴ʂ
    

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33. Mahout
    • gradle ‘org.apache.mahout:mahout-core:0.9'
    • https://github.com/apache/mahout
    • ˒ 229
    • ෼ࢄॲཧϑϨʔϜϫʔΫ Hadoop ্ͷػցֶशϥ
    ΠϒϥϦ
    • Spark / MLlib ͕ग़͖͔ͯͯΒ͍ͩͿΦϫίϯײ͕
    ᕷΈग़͖ͯͨؾ͕…
    

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34. SAMOA
    • https://github.com/yahoo/samoa
    • ˒ 363
    • Storm ͳͲͷ෼ࢄετϦʔϛϯάϑϨʔϜ
    ϫʔΫ্Ͱར༻Ͱ͖ΔػցֶशϥΠϒϥϦ
    • Yahoo! Labs ۘ੡
    • ̎͜͜ʙ̏ϲ݄͸͋·Γ։ൃ׆ൃͰͳ͍ʁ
    

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35. Jubatus
    • https://github.com/jubatus/jubatus
    • ˒ 389
    • ෼ࢄॲཧϑϨʔϜϫʔΫˍΦϯϥΠϯػցֶशϥΠϒ
    ϥϦ
    • ຊମ͸ C++ ࣮૷͕ͩɺJava ͷΫϥΠΞϯτϥΠϒϥ
    Ϧ͕ఏڙ͞Ε͍ͯΔ
    • ϦΞϧλΠϜॲཧͳػցֶश͕ཁٻ͞ΕΔ৔߹ʹద͠
    ͍ͯΔʁ
    

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36. h2o
    • https://github.com/h2oai/h2o
    • ˒ 1,333
    • ෼ࢄॲཧϑϨʔϜϫʔΫ Hadoop ্Ͱར༻Ͱ
    ͖ΔػցֶशϥΠϒϥϦ
    • Կ͔ͱ࿩୊ͷ Deep learning Λ Java Ͱ͍ͨ͠
    ͳΒɺ͜Ε୒Ұʂʁ
    

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37. ͸͡ΊͯΈΑ͏ػցֶश
    

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38. σʔληοτ
    

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39. UCI Machine learning repository
    • https://archive.ics.uci.edu/ml/datasets.html
    • ͍͍ͩͨ CSV ϑΝΠϧͰఏڙ͞Ε͍ͯΔ
    • ୅දతͳσʔληοτ
    • Mushroom: Ωϊί
    • ৭ɾܗঢ়ɾେ͖͞ͱ৯༻ɾ༗ಟͷϥϕϧ / ೋ஋෼ྨ
    • Iris: ΞϠϝσʔλ
    • ͕͘΍Ֆหͷ෯ɾ௕͞ͱ඼छͷϥϕϧ / ଟ஋෼ྨ
    • Abalone: ΞϫϏ
    • େ͖͞΍ॏ͞ͳͲͱ೥ྸ / ೥ྸͷ༧ଌ
    

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40. Weka Ͱ෼ྨɾճؼͯ͠ΈΔ
    

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41. http://bit.ly/jjug-­‐ml
    

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42. Weka ͷೖྗܗࣜ
    @RELATION iris
    @ATTRIBUTE sepallength NUMERIC
    @ATTRIBUTE sepalwidth NUMERIC
    @ATTRIBUTE petallength NUMERIC
    @ATTRIBUTE petalwidth NUMERIC
    @ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica}
    !
    @DATA
    5.1,3.5,1.4,0.2,Iris-setosa
    4.9,3.0,1.4,0.2,Iris-setosa
    4.7,3.2,1.3,0.2,Iris-setosa
    4.6,3.1,1.5,0.2,Iris-setosa
    5.4,3.9,1.7,0.4,Iris-setosa
    ……
    "3''ϑΝΠϧ
    

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43. Weka ͷೖྗܗࣜ
    @RELATION iris
    @ATTRIBUTE sepallength NUMERIC
    @ATTRIBUTE sepalwidth NUMERIC
    @ATTRIBUTE petallength NUMERIC
    @ATTRIBUTE petalwidth NUMERIC
    @ATTRIBUTE class {Iris-setosa,Iris-versicolor,Iris-virginica}
    !
    @DATA
    5.1,3.5,1.4,0.2,Iris-setosa
    4.9,3.0,1.4,0.2,Iris-setosa
    4.7,3.2,1.3,0.2,Iris-setosa
    4.6,3.1,1.5,0.2,Iris-setosa
    5.4,3.9,1.7,0.4,Iris-setosa
    ……
    "3''ϑΝΠϧ
    $47ϑΝΠϧΛΘ͟Θ͟ม׵͢Δͷ΋໘౗ʜ
    

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44. ࠓճ͸
    weka.core.converters.CSVLoader
    (Λͪΐͬͱ͍ͬͨ͡΋ͷ)
    Λ࢖͍·͢
    

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45. ར༻͍ͯ͠ΔΫϥεͷղઆ
    • weka.classifiers.Evaluation
    • k-෼ׂަࠩݕূΛ࣮ࢪ͢Δ
    • weka.classifiers.functions.Logistic
    • ϩδεςΟοΫճؼʹΑΔ෼ྨ
    • weka.classifiers.trees.RandomForest
    • RandomForest (ܾఆ໦ͷྨ) ʹΑΔ෼ྨ
    • weka.classifiers.functions.LinearRegression
    • ઢܗճؼ
    

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46. ࣮ࡍʹσϞͯ͠Έ·͢
    

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47. ͋Γ͕ͱ͏͍͟͝·ͨ͠ʂ
    

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