Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Prophetを使った時系列データ予測と機械学習モデルとの比較 / prophet-vs-ml
Search
Haruki Okuyama
October 27, 2019
Business
0
1.3k
Prophetを使った時系列データ予測と機械学習モデルとの比較 / prophet-vs-ml
時系列データにおいて, Prophetと3時間で作成した機械学習モデルとの精度比較
Haruki Okuyama
October 27, 2019
Tweet
Share
More Decks by Haruki Okuyama
See All by Haruki Okuyama
Prophetを使ったコスパの良い時系列データ予測 / prophet-use-cases
spring1018
0
110
Other Decks in Business
See All in Business
AI浅慮の時代における「考える」と「視点」、そして「創造性」
masayamoriofficial
1
1.8k
キャリアコンサルティングの継続利用がキャリア自律に及ぼす効果の検証
techtekt
PRO
1
130
Sprint Reviewで、ビジネスと開発の「当たり前」を同期する / RSGT2026
taguchimasahiro
0
1.9k
株式会社High Link_会社紹介資料
highlink_hr
2
80k
採用ピッチ資料
s_kamada
0
280
会社紹介資料 / ProfileBook
gpol
5
55k
株式会社TENET 会社紹介資料
tenetinc
1
22k
TAIAN Company Deck
taian
0
24k
Lego Agile Testing Workshop
pinboro
0
140
(15枚)NotebookLMのスライド生成機能で「絶対達成」「予材管理」「大量行動」の重要性を解説してもらう
nyattx
PRO
0
160
Akatsuki AI Technologies Company Deck
akatsuki_ai_technologies
0
590
Nulab Fun Deck 〜チームワークが、世界をもっと『おもしろく』する〜
nulabinc
PRO
1
1.8k
Featured
See All Featured
AI Search: Implications for SEO and How to Move Forward - #ShenzhenSEOConference
aleyda
1
1.1k
B2B Lead Gen: Tactics, Traps & Triumph
marketingsoph
0
53
Speed Design
sergeychernyshev
33
1.5k
Bootstrapping a Software Product
garrettdimon
PRO
307
120k
Art, The Web, and Tiny UX
lynnandtonic
304
21k
Building a Scalable Design System with Sketch
lauravandoore
463
34k
Marketing to machines
jonoalderson
1
4.6k
Scaling GitHub
holman
464
140k
How to audit for AI Accessibility on your Front & Back End
davetheseo
0
180
SEO Brein meetup: CTRL+C is not how to scale international SEO
lindahogenes
0
2.3k
Leo the Paperboy
mayatellez
4
1.4k
A better future with KSS
kneath
240
18k
Transcript
©2019 Wantedly, Inc. ProphetΛͬͨ࣌ܥྻσʔλ༧ଌͱ ػցֶशϞσϧͱͷൺֱ ML for Beginners! MeetUp #1
LTձ Oct 27, 2019 - Haruki Okuyama - @spring1018x
©2019 Wantedly, Inc. Self-Introduction •Haruki OkuyamaʢԞࢁ ݰكʣ •Chemistry Research (until
March 2019) •Wantedly, Inc. (since April 2019) •Recommendation Team • Mainly, Data Analysis
©2019 Wantedly, Inc. ͢͜ͱ ɾ౷ܭϞσϧͱػցֶशϞσϧͷ࣌ܥྻσʔλ༧ଌ ɾ࣌ܥྻ༧ଌϥΠϒϥϦProphetͷհ ͞ͳ͍͜ͱ ɾProphetͷৄࡉͳΞϧΰϦζϜ About this
talk
©2019 Wantedly, Inc. ɾֶशσʔλ(աڈ)ͱςετσʔλ(ະདྷ)ͷ͕ҟͳΔ ɾτϨϯυ͕͋Δͱ2ͭͷ͕ҟͳΔͷવ ɾػցֶशϞσϧΑΓ౷ܭϞσϧͷํ͕༧ଌਫ਼͕͍͍߹͋ͬͨΓ ͢ΔΒ͍͠* => ࣌ܥྻσʔλʹରͯ͠ػցֶशϞσϧͱ౷ܭϞσϧͷ༧ଌ݁ՌΛ ൺֱ͠,
ײ৮Λ͔֬Ί͍ͨʂ ࣌ܥྻσʔλͷ༧ଌͷ͠͞ *https://tjo.hatenablog.com/entry/2019/09/18/190000 https://t.co/S3BpRgtxUW?amp=1
©2019 Wantedly, Inc. ɾػցֶशϞσϧ ϥάಛྔΛத৺ʹ15ݸͷಛྔΛ࡞͠, LightGBMͰֶश ɾ౷ܭϞσϧ FacebookOSSͷProphetΛ༻ : ͋Δࢦඪ͕དྷ݄͍ͭ͘ʹͳΔ͔Λ༧ଌ͢Δ
* ͋Δͷ࣌Ͱ࣍ͷ݄ͷࢦඪΛ༧ଌ͍ͨ͠ ** 3࣌ؒ͘Β͍Ͱ༧ଌϞσϧΛ࡞͍ͨ͠
©2019 Wantedly, Inc. Prophetͬͯʁ 'BDFCPPLͷ044ඇઢܗͳ࣌ܥྻσʔλΛقઅੑٳޮՌΛऔΓೖΕͯ༧ଌ͢Δ ɾτϨϯυ g(t) ɾقઅੑ(पظੑ) s(t) ɾٳɾॕޮՌ
h(t) ɾΠϕϯτΩϟϯϖʔϯ Forecasting at Scale Sean J. Taylor∗† Facebook, Menlo Park, California, United States ࣌ܥྻσʔλΛ͜ΕΒͷཁૉͷͱߟ͑Δ (*ࣗݾ૬ؔߟྀ͍ͯ͠ͳ͍)
©2019 Wantedly, Inc. model࡞ Time 2016-01-01 ~ 2019-06-30·ͰͷσʔλΛֶͬͯश͠, modelΛ࡞ 2019-07-01
~ 2019-09-30ͰධՁ
©2019 Wantedly, Inc. modelධՁ Prophetͷํ͕ਫ਼͕ߴ͍ 2016-01-01 ~ 2019-06-30·ͰͷσʔλΛֶͬͯश͠, modelΛ࡞ 2019-07-01
~ 2019-09-30ͰධՁ Prophet ML MAPE: 12.2% MAPE: 10.6%
©2019 Wantedly, Inc. ͜͜·Ͱͷ·ͱΊ ɾτϨϯυɾपظੑͷڧ͍࣌ܥྻσʔλʹରͯ͠, ػցֶशϞσϧͷ߹, ࣌ؒͰਫ਼Λग़͢ͷ͍͠ ɾͬͱ࣌ؒΛ͔͚ΒΕΔ߹ಛྔઃܭɾόϦσʔγϣϯͷͷ༨ ͕͋ΔͷͰ࣌ܥྻϞσϧʹউͯͦ͏
©2019 Wantedly, Inc. Prophet: ֤ཁૉͷӨڹ ɾτϨϯυ g(t) ɾقઅੑ s(t) ɾٳɾॕޮՌ
h(t) ɾΠϕϯτΩϟϯϖʔϯ ɾٳॕ͚ͩͰͳ͘, ҙͷΠϕϯτΩϟϯϖʔϯͷޮՌऔΓೖΕΔ͜ͱ͕Ͱ͖Δ ɾ͞Βʹ, ֤ཁૉͷӨڹఆྔతʹࢉग़Ͱ͖Δ
©2019 Wantedly, Inc. Prophet: ֤ཁૉͷӨڹ τϨϯυ, ༵ɾ݄ͷӨڹ, ॕͷӨڹͷՄࢹԽ ॱௐʹ Լ
3্݄ঢ trend holiday weekly yearly ॕԼ
©2019 Wantedly, Inc. Prophetͷಛ ɾτϨϯυɾपظੑͷڧ͍࣌ܥྻσʔλʹ͍͍ͯΔ ɾ֤ͷӨڹ͕ఆྔతʹѲͰ͖ΔͷͰઆ໌ੑ͕ߴ͍ ɾύϥϝʔλνϡʔχϯάͦΕ΄Ͳඞཁͳ͍ ɾతͱ͢ΔࢦඪͷυϝΠϯࣝ͑͋͞ΕΑ͍. ྫ༵͑पظ͕͋Δ, ࿈ٳԼ͢Δetc
©2019 Wantedly, Inc. ɾ࣌ܥྻσʔλ༧ଌʹ͓͚ΔػցֶशϞσϧͱProphetͷൺֱ ɾઃఆ͔͚ΒΕΔ࣌ؒΛߟྀͯ͠બ͢Δ ɾProphetʹΑΔ༧ଌ ɾखܰʹ࣌ܥྻ༧ଌ͕Մೳ ɾυϝΠϯ͕ࣝ͋ΕपظɾΠϕϯτޮՌͷઃఆʹΑΓਫ਼্͕͕Δ ɾσʔλΛߏ͢ΔཁૉͷӨڹ͕ఆྔతʹΘ͔Δ Summary