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
Lasso.pdf
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
kichinosukey
December 26, 2018
0
56
Lasso.pdf
スパーシティ大事。以下の本の理解を残したくて。著者の方には感謝しかないです。
https://www.sbcr.jp/products/4797393965.html
kichinosukey
December 26, 2018
Tweet
Share
More Decks by kichinosukey
See All by kichinosukey
カーネル関数とは
kichinosukey
0
54
Latin Hypercube Sampling
kichinosukey
0
73
NSGAII
kichinosukey
0
51
NSGA
kichinosukey
0
55
基底関数回帰の概要について
kichinosukey
0
77
児童虐待の現状
kichinosukey
0
62
イノベーションのジレンマとフィンテック
kichinosukey
0
73
Paxos made simpleを理解しよう
kichinosukey
0
510
Featured
See All Featured
Mozcon NYC 2025: Stop Losing SEO Traffic
samtorres
0
140
HDC tutorial
michielstock
1
350
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
46
2.7k
Writing Fast Ruby
sferik
630
62k
The Pragmatic Product Professional
lauravandoore
37
7.1k
The Cult of Friendly URLs
andyhume
79
6.8k
Paper Plane (Part 1)
katiecoart
PRO
0
4k
It's Worth the Effort
3n
188
29k
Jamie Indigo - Trashchat’s Guide to Black Boxes: Technical SEO Tactics for LLMs
techseoconnect
PRO
0
55
Claude Code のすすめ
schroneko
67
210k
Ruling the World: When Life Gets Gamed
codingconduct
0
140
30 Presentation Tips
portentint
PRO
1
210
Transcript
-BTTP
֓ཁ ↟-ϓϰϥΤᩆ᳀ặḄͺͩ൰͚ͱᤎ᷀ᙚΤᱠᖀặͫΝ φ = 1 2 y − ˜ Xω
+ λ ω1 ω1 = d ∑ i=1 ωi
ղ๏֓ཁ ↟᫉ᶝ෦᷀ď$PPSEJOBUF%FTDFOUĐ ↟ؔȃ Y ΤᱠᖀặͫΝͱΓfᤎ᷀ΤຬͱͫḑΤᄌͱ͖ ↟ͩͩ͝ჯᙉͽ᧶ḑΤᄌΝͥͺီ͖ͩf᧱ͼᰮᲩ͝Λξ τ⑲ύͩᓓᙚΤ᙮͖ͩ͡ ↟᧱ͼᰮᲩ ∂φ ∂xi
= 0, (j = 1,…, d) X(0) = (x(0) 1 , x(0) 2 , …, x(0) d )
ղ๏֓ཁ ↟ᤎ᷀ΤຬͱͫΚ͘ͼYΤཏΓfͯΞΤY? L ͺͫΝ ↟ჯ༷ͽ ↟ᓓᙚͶfᵟዸᐠፖᩔᙚΤYͲͣხͩ͝ḑͥ͘ͺ͖ͩΝ ↟ͶมͲͣხͩ͝ͽͼΞᱠ᧱ḑ࿄ᑾͽͼΝͺ͖͘ວ͚ ∂φ ∂x1
(x1 , x(k) 2 , …, x(k) d ) = 0 ∂φ ∂x2 (x(k+1) 1 , x2 , …, x(k) d ) = 0
ղ๏ ↟ͩͩ͝fϮψςȃዸᐠᏵ൱ၙďθϮϥࢀ᪑Đ ↟ͯΐΐ$%͞ᑿ͚ͼ͖ ↟ᠻf᫈ͽᐠᷡͩᵟዸᐠΤḝ͘
ίϥϜ ↟Z]Y]ዸᐠ͟ͼ͖Ħ ↟ᤎ᷀ᙚΚΜᅻଓᕥຬͱͧΞΝ ↟ͩͩ͝ᤎ᷀ΚΜྵᲩ᪰ͩ͞ͼ͖ͱΓͯΐΐዸᐠ͟ͼ͖ lim n→0 f(h) = f(0) =
0 lim h→+0 |x + h| − |x| h = lim h→+0 (x + h) − x h = 1 lim h→−0 |x + h| − |x| h = lim h→+0 −(x + h) − (−x) h = − 1
ղ๏ৄࡉ ↟ᥦᅪḑ͟͟Ξͼ͖ᬊᙚΤᷡᛔhhh ↟ᱠ᪾᧣ͽX@L? X@L?ዸᐠፖᩔᙚḑX@L᙮Ꮞͺͩᑿ ΡΞΝ ↟X@L? X@L X@L?X@LΤ᧸ᩮͺͫΝ ↟X@L? ͺX@L?Τຬͱͧͼ͖ᦉᷯ
X@L ᙮ͩͼ͖ ↟᙮ἦX@LᲩᤎ᷀ͺͼΝ ˜ ωk = S (∑n i=1 (yi − ω0 − ∑ j≠k xi ωj )xik , λ) ∑n i=1 x2 ik ωk
ղ๏ৄࡉ ↟X@L? ͺͼΝͽ ↟X@L?ͺͼΝͽ ↟ͯͩᤎ᷀ᙉX@L? ͝ͶX@L?͔Ν ωk > λ ωk
< − λ −λ < ωk < λ
ιϑτᮢؔ4 ↟THOᐊ߸ؔͺṺΞΝ ↟THO Y Y Y S(p, q)
= sgn(p) max{0, ∥p∥ − q}
ιϑτᮢؔͷಛ ↟X@L᙮͝Λξτ⑲ύ ↟Ϯψςḑၞ͡͞ͺͼΝᔬͻǹX@Lǹฒ᷀ͽͯΞΛ ͔͞ΝͱΓďਤ੨ᔻĐ
ϋΠύʔύϥϝʔλͷޮՌ