ランダムフォレストを使って探索的データ分析

Transcript

1. ϥϯμϜϑΥϨετΛ࢖ͬͯ ୳ࡧతσʔλ෼ੳ
2. Presenter ੢ా צҰ࿠ co-founder/ceo Exploratory ུྺ Exploratory, Inc.ͰCEO݉νʔϑɾϓϩμΫτɾΦ ϑΟαʔΛ຿ΊΔ͔ͨΘΒɺ೔ຊͰͷσʔλαΠΤϯ εɾϒʔτΩϟϯϓɾτϨʔχϯά ɺάϩʔόϧͷσʔ λαΠΤϯεɾϒʔελʔɾτϨʔχϯάͳͲͷ৔Λ ௨ͯ͠σʔλαΠΤϯεͷීٴͱڭҭʹऔΓ૊Ήɻ @KanAugust
3. Exploratory Data Analysis with Random Forest
4. Exploratory Data Analysis with Random Forest
5. ܾఆ໦ σʔλ αϯϓϧ αϯϓϧ αϯϓϧ ౤ථ ౤ථ ౤ථ ݁࿦ … ϥϯμϜαϯϓϧ ౤ථׂ͕Εͨ৔߹ฏۉΛͱΓɺ ֬཰ͱͯ͠ѻ͏ ϥϯμϜϑΥϨετ
6. ϥϯμϜϑΥϨετͬͯɺ༧ଌͷͨΊ͡Όͳ͍ͷʁ
7. Employee Is_Salesrep Is_Male Attrition A TRUE FALSE TRUE B FALSE TRUE TRUE C TRUE FALSE FALSE D FALSE FALSE FALSE E TRUE TRUE TRUE Z TRUE TRUE ? ͜ͷैۀһ͸ࣙΊΔͰ͠ΐ͏͔ʁ ෼ྨ - ܾఆ໦
8. Is_Salesrep TRUE FALSE Is_Male TRUE FALSE … TRUE FALSE TRUE FALSE Z FALSE TRUE ? Employee Is_Salesrep Is_Male Attrition A TRUE FALSE TRUE B FALSE TRUE TRUE C TRUE FALSE TRUE D FALSE FALSE FALSE E FALSE TRUE TRUE ࣙΊΔʁ ࣙΊΔ ࣙΊͳ͍ ࣙΊΔ ෼ྨ - ܾఆ໦
9. … TRUE FALSE TRUE FALSE X TRUE TRUE ? Employee Is_Salesrep Is_Male Attrition A TRUE FALSE TRUE B FALSE TRUE TRUE C TRUE FALSE TRUE D FALSE FALSE FALSE E FALSE TRUE TRUE ࣙΊΔ ࣙΊͳ͍ ࣙΊΔ Is_Salesrep Is_Male ࣙΊΔʁ ෼ྨ - ܾఆ໦
10. TRUE FALSE TRUE FALSE … TRUE FALSE TRUE FALSE X TRUE TRUE TRUE Employee Is_Salesrep Is_Male Attrition A TRUE FALSE TRUE B FALSE TRUE TRUE C TRUE FALSE TRUE D FALSE FALSE FALSE E FALSE TRUE TRUE ࣙΊΔ ࣙΊͳ͍ ࣙΊΔ Is_Salesrep Is_Male ࣙΊΔʁ ෼ྨ - ܾఆ໦
11. Ͳͷม਺ΛઌʹධՁ͢Δ͔Ͱ༧ଌ݁Ռ͕ૣ͘ಘΒΕΔ
12. ͜ͷ৘ใΛ΋ͱʹ ม਺ॏཁ౓(Variable Importance)͕ ಘΒΕΔ
13. RF Model
14. ม਺ॏཁ౓
15. Ͳͷม਺͕ଞͷม਺ʹൺ΂ͯॏཁ͔͸෼͔ͬͨ
16. ͔͠͠… ͦͷม਺͕Ͳ͏Өڹ͍ͯ͠Δͷ͔͕Α͘෼͔Βͳ͍
17. Job Level
18. Monthly Income
19. ͦ͜Ͱ… edarf - EDA with RandomForest ύοέʔδ
21. Partial Dependency
22. Job Level Monthly Income Stock Option 1 5000 1 3 10000 2 2 4000 1 2 6000 2 3 50000 3 … 1 5000 2 ݩͷσʔλ͔Β
23. Job Level Monthly Income Stock Option 1 5000 1 3 10000 2 2 4000 1 2 6000 2 3 50000 3 αϯϓϧ͢Δ
24. Job Level Monthly Income Stock Option 1 5000 1 1 10000 2 1 4000 1 1 6000 2 1 50000 3 Job Level͕̍ɼ̎ɼ̏ͷ̏ͭͩͱ͢Δͱɺ ͜ͷྻͷ஋͚ͩΛม͑ɺଞͷྻ͸ͦͷ··ͰɺγϛϡϨʔτ͢Δ Job Level Monthly Income Stock Option 2 5000 1 2 10000 2 2 4000 1 2 6000 2 2 50000 3 Job Level Monthly Income Stock Option 3 5000 1 3 10000 2 3 4000 1 3 6000 2 3 50000 3
25. Job Level Monthly Income Stock Option 1 5000 1 1 10000 2 1 4000 1 1 6000 2 1 50000 3 Job Level͕̍ͷ৔߹ RF Model Job Level Monthly Income Stock Option Prediction Probability 1 5000 1 0.3 1 10000 2 0.7 1 4000 1 0.2 1 6000 2 0.1 1 50000 3 0.6 0.38 ฏۉ஋
26. Job Level Monthly Income Stock Option 2 5000 1 2 10000 2 2 4000 1 2 6000 2 2 50000 3 Job Level Monthly Income Stock Option Prediction Probability Predict 2 5000 1 0.2 2 10000 2 0.3 2 4000 1 0.1 2 6000 2 0.1 2 50000 3 0.3 RF Model Job Level͕̎ͷ৔߹ 0.2 ฏۉ஋
27. Job Level Monthly Income Stock Option 3 5000 1 3 10000 2 3 4000 1 3 6000 2 3 50000 3 Job Level Monthly Income Stock Option Prediction Probability 3 5000 1 0.2 3 10000 2 0.3 3 4000 1 0.1 3 6000 2 0.1 3 50000 3 0.3 RF Model Job Level͕̏ͷ৔߹ 0.2 ฏۉ஋
28. ϓϩοτ͢Δ FALSE TRUE
29. with RStudio
30. with Exploratory
32. σʔλαΠΤϯεɾϒʔτΩϟϯϓ τϨʔχϯά݄̏։࠵ https://exploratory.io/training-jp
33. ࿈བྷઌ Email support@exploratory.io Website https://ja.exploratory.io Twitter @ExploratoryData Facebook ExploratoryJapan