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
Rで有名絵画を安全に買いたい
Search
saltcooky
September 16, 2022
Science
420
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Rで有名絵画を安全に買いたい
TokyoR #101 LT
saltcooky
September 16, 2022
More Decks by saltcooky
See All by saltcooky
SpatialRDDパッケージによる空間回帰不連続デザイン
saltcooky12
0
300
動的トリートメント・レジームを推定するDynTxRegimeパッケージ
saltcooky12
0
300
FIBA W杯の日本代表って組み合わせ次第で2次ラウンド行けたんじゃね?をデータで検証
saltcooky12
0
360
階層クラスタリングにおける仮説検定
saltcooky12
0
1.1k
データドリブンな仮説検証のためのSelective Inference
saltcooky12
1
1.5k
ストリートスナップデータに 統計的ネットワーク分析の適用を試みた
saltcooky12
0
900
Other Decks in Science
See All in Science
[NLP2026 参加報告会] AI for Science まとめ / NLP2026
lychee1223
0
2k
Non-Gaussian, nonlinear causal discovery with hidden variables and application
sshimizu2006
0
180
Testing the Longevity Bottleneck Hypothesis
chinson03
0
450
機械学習 - DBSCAN
trycycle
PRO
0
2.1k
How a camera trap data standard enabled an ecosystem of interoperable tools
peterdesmet
0
130
摂理と合理の肉体改造 — AI時代の減量を支える観測・制御・継続
kiyoshi
0
3.4k
「遂行理論の未来」(松島斉教授最終講義記念セッションの発表資料)
shunyanoda
0
990
コーヒー豆様核 (Coffee-bean nuclei) における形態学的サブタイピングと精選・焙煎特性の同定
jagupath
PRO
0
160
JSAI2026企画セッションKS-14 インタビュー集『⼈⼯知能と哲学と四つの問い』が提起する⼈⼯知能のこれからの課題 趣旨説明 / JSAI2026 Special Session: A Collection of Interviews, “Artificial Intelligence, Philosophy, and Four Questions”
ykiyota
0
440
データベース05: SQL(2/3) 結合質問
trycycle
PRO
0
1.3k
生成AI・プレプリント時代における 研究成果公開の再設計 ― トップカンファレンス文化はどこへ向かうのか / Redesigning the Dissemination of Research Outputs in the Age of Generative AI and Preprints — Where Is the Top-Conference Culture Heading?
ykiyota
0
30k
ゲームと人工知能
miyayou
0
180
Featured
See All Featured
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
46
3k
Build your cross-platform service in a week with App Engine
jlugia
234
19k
Ecommerce SEO: The Keys for Success Now & Beyond - #SERPConf2024
aleyda
1
2.1k
GraphQLの誤解/rethinking-graphql
sonatard
75
12k
HU Berlin: Industrial-Strength Natural Language Processing with spaCy and Prodigy
inesmontani
PRO
0
680
Done Done
chrislema
186
16k
Primal Persuasion: How to Engage the Brain for Learning That Lasts
tmiket
0
440
Fireside Chat
paigeccino
42
4k
Imperfection Machines: The Place of Print at Facebook
scottboms
270
14k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
133
19k
How to train your dragon (web standard)
notwaldorf
97
6.8k
Public Speaking Without Barfing On Your Shoes - THAT 2023
reverentgeek
1
560
Transcript
3Ͱ༗໊ֆըΛ҆શʹങ͍͍ͨ !TBMUDPPLZ 5PLZP3 1
୭ʁ 2 !TBMUDPPLZ • 3ྺɿ͙Β͍͔ͳ • ۈઌɿຊʹ͋Δ*5ܥͷձࣾ • ࣄ༰ɿ3%తͳ෦ॺͰ
ɹɹɹ3Λͬͨσʔλੳ͞Μ ػցֶशͷॲཧ࡞ • झຯɿϑΝογϣϯඒज़ؗ८Γ
δϟΫιϯϙϩοΫΛ͍ͬͯ·͔͢ 3 +BDLTPO1PMMPL நදݱओٛͷදతͳΞϝϦΧਓըՈ
δϟΫιϯϙϩοΫΛ͍ͬͯ·͔͢ 4 υϩοϓϖΠϯςΟϯά
δϟΫιϯϙϩοΫΛ͍ͬͯ·͔͢ 5 ʰ/P ʱ ºNN
δϟΫιϯϙϩοΫΛ͍ͬͯ·͔͢ 6 ʰ/P ʱ ºNN ݄ ݱඒज़࠷ߴֹ ࣌ ԯສυϧ
δϟΫιϯϙϩοΫΛ͍ͬͯ·͔͢ 7 ཉ͍͠ʂ
δϟΫιϯϙϩοΫΛ͍ͬͯ·͔͢ 8 ͚Ͳɺِଟͦ͏ʜ
ϙϩοΫͷֆըΛղੳͨ͠ݚڀ 9 • Fractal analysis of Pollock’s drip paintings.
(R.P.Taylor, et al , 1999) • On multifractal structure in non-representational art. (J.R.Nureika, et al , 2005) ˠϙϩοΫͷυϩοϓϖΠϯςΟϯάʹ ϑϥΫλϧߏ͕͋Δ͜ͱ͕Θ͔Δ
ϑϥΫλϧߏ 10 ਤܗͷҰ෦Λ֦େ͢Δͱɺશମͱ૬ࣅ͢Δܗ ࣗݾ૬ࣅੑ ͕ଘࡏ͢Δߏ FYγΣϧϐϯεΩʔͷΪϟεέοτ
ϑϥΫλϧ࣍ݩ ༰ྔ࣍ݩϋυϧϑ࣍ݩ 11 w ͲΕ͚ͩࣗݾ૬ࣅੑ͕͋Δ͔Λࣔ͢ྔ w ֤ۭؒํʹ-ʹॖΊΔͱɺͱͷਤܗΛຒΊΔʹ/-%ݸ ͷࣗݾ૬ࣅਤܗ͕ඞཁͱ͍͏͜ͱΛදݱ w
ʙͷؒΛͱΓɺʹ͍ۙ΄Ͳࣗݾ૬ؔੑ͕ڧ͍ w γΣϧϐϯεΩʔͷΪϟεέοτͷ࣍ݩ w ղੳతʹ#PY$PVOUJOHΞϧΰϦζϜʹΑΓਪఆ
#PY$PVOUJOHΞϧΰϦζϜ 12 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ ̍ରը૾ΛҰลͷ͕͞-ͷϒϩοΫʹ͚Δ
#PY$PVOUJOHΞϧΰϦζϜ 13 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ ̍ରը૾ΛҰลͷ͕͞-ͷϒϩοΫʹ͚Δ
#PY$PVOUJOHΞϧΰϦζϜ 14 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ ̎ର͕өΓࠐΜͰ͍ΔϒϩοΫͷ/ - Λ͑Δ
#PY$PVOUJOHΞϧΰϦζϜ 15 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ ϒϩοΫେ͖͞-Λখͯ͘͞͠ରը૾Λ͚Δ
#PY$PVOUJOHΞϧΰϦζϜ 16 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ ର͕өΓࠐΜͰ͍ΔϒϩοΫͷ/ - Λ͑Δ
#PY$PVOUJOHΞϧΰϦζϜ 17 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ େ͖͞-Λখ͘͞͠ͳ͕Βର͕өΔϒϩοΫΛΧϯτ͢Δ ɹ͜ͱΛ܁Γฦ͢
#PY$PVOUJOHΞϧΰϦζϜ 18 ϑϥΫλϧ࣍ݩΛٻΊΔྲྀΕ ϒϩοΫͷେ͖͞-ͱΧϯτ/ - ͷ྆ରάϥϑʹ͓͚Δ ɹճؼઢͷ͖͕ϑϥΫλϧ࣍ݩʹͳΔ log N(L)
= D log(L) + K ʢ,ఆʣ MPH/ - MPH- ޯ%ʹ ϑϥΫλϧ࣍ݩ
19 w ͳͥ͜ΕͰϑϥΫλϧ࣍ݩΛਪఆ͢Δ͜ͱ͕Ͱ͖Δͷ͔ ఆ͔ٛΒͷมܗ log N(L) = log( a
L )D log N(L) = D log(L) + D log(a) #PY$PVOUJOHΞϧΰϦζϜ ʢBɿਖ਼ͷఆʣ
20 δϟΫιϯϙϩοΫͷ࡞ͷ߹ w -DNͰϑϥΫλϧ࣍ݩ͕มԽ w %% -Ҏ্ %- -ະຬ ʰ#MVF1PMFT/VNCFS
ʱ MPH - NN MPH / #PY$PVOUJOHΞϧΰϦζϜ
ϙϩοΫͷֆըͷಛ 21 ʢ̍ʣ̎छͷϑϥΫλϧύλʔϯ͔ΒΔ ʢ̎ʣ༷ʑͳεέʔϧʹ͓͍ͯϑϥΫλϧੑ͕ଘࡏ ʢ̏ʣϑϥΫλϧ࣍ݩରάϥϑͷޯ͔ΒٻΊΕΔ ʢ̐ʣ%-ʼ%% ʢ̑ʣۙࣅۂઢͷඪ४ภ͕ࠩখ͍͞ d ʢ̒ʣ֤৭ͷͰ্هͷ̑ͭͷಛΛຬͨ͢
3Ͱ#PY$PVOUJOH 22 7PY31BDLBHF
3Ͱ#PY$PVOUJOH 23 γΣϧϐϯεΩʔͷΪϟεέοτͷϑϥΫλϧ࣍ݩΛٻΊΔ ը૾ॲཧ
3Ͱ#PY$PVOUJOH 24 γΣϧϐϯεΩʔͷΪϟεέοτͷϑϥΫλϧ࣍ݩΛٻΊΔ ϑϥΫλϧ࣍ݩΛٻΊΔ
3Ͱ#PY$PVOUJOH 25 γΣϧϐϯεΩʔͷΪϟεέοτͷϑϥΫλϧ࣍ݩΛٻΊΔ ྆ରάϥϑͱճؼઢͷՄࢹԽ 0 2 4 6 8 -7
-6 -5 -4 -3 -2 log(1/res) log(N) Box Counting method : D=1.5747
؆୯ʹ·ͱΊ 26 w δϟΫιϯϙϩοΫͷֆըʹϑϥΫλϧߏ͕ଘࡏ͢Δ w ϑϥΫλϧߏͷϑϥΫλϧ࣍ݩΛղੳతʹٻΊΔͨΊʹ ɺ#PY$PVOUJOHΞϧΰϦζϜΛ༻͍Δ w
3Ͱ7PY3QBDLBHFͷCPY@DPVOUJOHؔͰ࣮ߦͰ͖Δ
&/% 27 &OKPZ
ࢀߟࢿྉ 28 •RʹΑΔը૾ॲཧɿimagerύοέʔδͷ͍ํ https://htsuda.net/archives/1985 •ϘοΫεΧϯτ๏ʹΑΔඐഀބͷϑϥΫλϧ࣍ݩ https://shiga-u.repo.nii.ac.jp/?action=repository_uri&item_id=1751