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
ベイズで単回帰モデルを考える /bayes-simple-linear-regression
Search
Thimblee
November 09, 2022
Technology
0
290
ベイズで単回帰モデルを考える /bayes-simple-linear-regression
Thimblee
November 09, 2022
Tweet
Share
More Decks by Thimblee
See All by Thimblee
巡回セールスマン問題での貪欲法の精度 / accuracy of greedy method in TSP
thimblee
0
930
Other Decks in Technology
See All in Technology
サイバーエージェントグループのSRE10年の歩みとAI時代の生存戦略
shotatsuge
4
1.1k
ポストコロナ時代の SaaS におけるコスト削減の意義
izzii
1
470
Digitization部 紹介資料
sansan33
PRO
1
4.5k
PHPからはじめるコンピュータアーキテクチャ / From Scripts to Silicon: A Journey Through the Layers of Computing
tomzoh
2
150
名刺メーカーDevグループ 紹介資料
sansan33
PRO
0
820
Deep Security Conference 2025:生成AI時代のセキュリティ監視 /dsc2025-genai-secmon
mizutani
4
3k
AIコードアシスタントとiOS開発
jollyjoester
0
120
ClaudeCodeにキレない技術
gtnao
1
870
AIエージェントが書くのなら直接CloudFormationを書かせればいいじゃないですか何故AWS CDKを使う必要があるのさ
watany
19
7.6k
AWS Well-Architected から考えるオブザーバビリティの勘所 / Considering the Essentials of Observability from AWS Well-Architected
sms_tech
1
160
How Do I Contact Jetblue Airlines® Reservation Number: Fast Support Guide
thejetblueairhelpsupport
0
150
〜『世界中の家族のこころのインフラ』を目指して”次の10年”へ〜 SREが導いたグローバルサービスの信頼性向上戦略とその舞台裏 / Towards the Next Decade: Enhancing Global Service Reliability
kohbis
3
1.5k
Featured
See All Featured
The Invisible Side of Design
smashingmag
301
51k
Performance Is Good for Brains [We Love Speed 2024]
tammyeverts
10
980
How STYLIGHT went responsive
nonsquared
100
5.6k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
47
9.6k
GitHub's CSS Performance
jonrohan
1031
460k
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
50
5.5k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
130
19k
Gamification - CAS2011
davidbonilla
81
5.4k
CoffeeScript is Beautiful & I Never Want to Write Plain JavaScript Again
sstephenson
161
15k
Connecting the Dots Between Site Speed, User Experience & Your Business [WebExpo 2025]
tammyeverts
8
340
Done Done
chrislema
184
16k
Building Flexible Design Systems
yeseniaperezcruz
328
39k
Transcript
ϕΠζͰ୯ճؼϞσϧΛߟ͑Δ 5IJNCMFF 1
ઃఆ ܇࿅σʔλͷઆ໌ม ͱతม ͔ΒҎԼͷ ༧ଌΛٻΊΔ ҎԼͷ୯ճؼϞσϧΛ༻͢Δ x = (x1
, x2 , ⋯, xN )T t = (t1 , t2 , ⋯, tN )T p(t* |x* , t, x) p(t* |x* , w, β) = 𝒩 (t* |w0 + w1 x* , β−1) 2
۩ମతʹ ͜͏͍͏σʔλʹର͍͍ͯ͠ײ͡ʹύϥϝʔλ Λௐͯ͠ɺઢ ΛҾ͖͍ͨɻ͜ͷσʔλେମ ͱͳ͍ͬͯΔɻ w = (w0 , w1
)T y = w0 + w1 x t = − 2 + 2x 3
ϕΠζͷఆཧ p(A|B) = p(A)p(B|A) p(B) 4
ࣄޙ QPTUFSJPS ύϥϝʔλɺ σʔλ ࣄޙΛ༻͍ͨύϥϝʔλͷਪఆ͕ϕΠζਪఆͰ͢ɻ w t p(w|t)
= p(w)p(t|w) p(t) ∝ p(w)p(t|w) (posterior) ∝ (prior)(likelihood) 5
ࣄલ QSJPS p(w) = 𝒩 (w|0, α−1I), α =
0.25 6
ؔ MJLFMJIPPE L(w) = p(t|w) = 𝒩 (t|m, β−1I)
where m = (w0 + w1 x1 , w0 + w1 x2 , ⋯, w0 + w1 xN )T, β = 2.0 7
ؔͷྫ ͜ͷΑ͏ͳ͍͍ײ͡ͷઢͩͱͱ͍͏େ͖͍ΛͱΔ L((−2.1,2.2)T) = 0.39 8
ؔͷྫ ͜ͷΑ͏ͳઢͩͱͱ͍͏ΛͱΔ L((−1.0,0.0)T) = 0.29 9
ؔͷྫ ͜ͷΑ͏ͳѱ͍ઢͩͱͱ͍͏খ͍͞ΛͱΔ L((1.0, − 3.0)T) = 0.18 10
ࣄલͱؔʢ࠶ܝʣ ؔ MJLFMJIPPE ࣄલ QSJPS 11
ࣄલͱؔͷੵ 12
ٻΊΒΕͨઢ ࣄޙ ͷ࣌ʹ࠷େʹͳΔ w = (−1.08,0.38) L((−1.08,0.38)T) = 0.31
13
͚ؔͩʢ࠷ਪఆʣͰ͍͍ͷͰ ϕΠζʢࣄޙʣͩͱσʔλΛ͏·͘දݱͰ͖͍ͯͳ͍ ࣮ࡍɺ͜ͷσʔλΛ୯ճؼϞσϧͰֶश͢ΔࡍʹϕΠζඞཁͳ͍ ʢ୯ճؼϞσϧ͕ཧղ͍͔͢͠Β༻͍ͨʣ ͔͠͠ɺҰൠʹϕΠζͰߟ͑ΔϝϦοτ͕ଟ͍ 14
ϕΠζͷಛ w ύϥϝʔλʢ୯ճؼϞσϧͳΒ ʣʹ͍ͭͯ֬Λߟ͑ΒΕΔ w ࣄલʹʢσʔλҎ֎ͷʣطͷใΛөͤ͞ΒΕΔ w ֬ͷஞ࣍ߋ৽͕Ͱ͖Δ w աֶशΛ͛Δʢਖ਼ଇԽʣ
w ʢଞʹ৭ʑ͋Δͱࢥ͍·͢ʣ w 15
͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠ 16