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
Receiver Operator Characteristic Curve
Search
Shoh-kudo
June 19, 2019
Education
1
60
Receiver Operator Characteristic Curve
はじめての『はじめてのパターン認識』第3章
A first introduction of ROC curve (Section 3.2).
Shoh-kudo
June 19, 2019
Tweet
Share
More Decks by Shoh-kudo
See All by Shoh-kudo
Principal Component Analysis; PCA
shoh0320
0
45
Support Vector Machine (SVM)
shoh0320
0
120
Newton method
shoh0320
0
45
Other Decks in Education
See All in Education
『会社を知ってもらう』から『安心して活躍してもらう』までの プロセスとフロー
sasakendayo
0
230
Education-JAWS #3 ~教育現場に、AWSのチカラを~
masakiokuda
0
160
生成AI
takenawa
0
4.5k
Data Processing and Visualisation Frameworks - Lecture 6 - Information Visualisation (4019538FNR)
signer
PRO
1
2.4k
子どものためのプログラミング道場『CoderDojo』〜法人提携例〜 / Partnership with CoderDojo Japan
coderdojojapan
4
16k
Visualisation Techniques - Lecture 8 - Information Visualisation (4019538FNR)
signer
PRO
0
2.4k
Tangible, Embedded and Embodied Interaction - Lecture 7 - Next Generation User Interfaces (4018166FNR)
signer
PRO
0
1.7k
View Manipulation and Reduction - Lecture 9 - Information Visualisation (4019538FNR)
signer
PRO
1
2k
Tutorial: Foundations of Blind Source Separation and Its Advances in Spatial Self-Supervised Learning
yoshipon
1
110
バックオフィス組織にも「チームトポロジー」の考えが使えるかもしれない!!
masakiokuda
0
110
技術文章を書くための執筆技術と実践法(パラグラフライティング)
hisashiishihara
18
6.5k
IMU-00 Pi
kanaya
0
360
Featured
See All Featured
BBQ
matthewcrist
89
9.7k
Code Reviewing Like a Champion
maltzj
524
40k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
29
2.7k
Large-scale JavaScript Application Architecture
addyosmani
512
110k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
130
19k
Why Our Code Smells
bkeepers
PRO
337
57k
A Modern Web Designer's Workflow
chriscoyier
693
190k
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
657
60k
Optimising Largest Contentful Paint
csswizardry
37
3.3k
The Straight Up "How To Draw Better" Workshop
denniskardys
233
140k
Put a Button on it: Removing Barriers to Going Fast.
kastner
60
3.9k
The Cult of Friendly URLs
andyhume
79
6.5k
Transcript
ୈষϕΠζͷࣝผنଇ ड৴ऀಈ࡞ಛੑۂઢ ͡Ίͯͷύλʔϯೝࣝྠಡձ ౻ 1
065-*/& ϕΠζͷࣝผنଇ ࠞಉߦྻ ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ষ ·ͱΊ ຕ ຕ ຕ ຕ
ຕ !2
ϕΠζͷࣝผنଇ ٤Ԏ͍ͯ͠Δਓ͕͍ͨʜ පؾͩͬͨʜ Cd P(Cd |x) = p(x|Cd )P(Cd )
p(x) ݈߁ͩͬͨ Ch P(Ch |x) = p(x|Ch )P(Ch ) p(x) ࣝผΫϥε = argmax p(x|Ci )P(Ci ) i x !3
ϕΠζͷࣝผنଇ ࣝผΫϥε = argmax p(x|Ci )P(Ci ) i ϵ(x) =
min [P(Ci |x)] ΫϥεΛޡΔ֬ʢසʣ i පؾͩͬͨʜ Cd P(Cd |x) = p(x|Cd )P(Cd ) p(x) ݈߁ͩͬͨ Ch P(Ch |x) = p(x|Ch )P(Ch ) p(x) !4
ϕΠζͷࣝผنଇ පؾͩͬͨʜ Cd ݈߁ͩͬͨ Ch ຊ݈߁ͩͬͨͷʹ පؾͩͱݴͬͯ͠·ͬͨ ຊපؾͩͬͨͷʹ ݈߁ͩͱݴͬͯ͠·ͬͨ ِӄੑ
ِཅੑ ࣝผڥք !5 ϵ(x) = min [P(Ci |x)] ΫϥεΛޡΔ֬ʢසʣ i පؾͰ͋Δ͜ͱΛཅੑͱ͢Δͱ
පؾͩͬͨʜ Cd ݈߁ͩͬͨ Ch ϕΠζͷࣝผنଇ ࣝผΫϥε = argmax p(x|Ci )P(Ci
) i ࠞಉߦྻ ࣝผͷੑೳΛͲ͏ධՁ͢Δ͔ !6
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ͜ΕΒͷΛͬͯࣝผੑೳΛධՁ͢Δ !7
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ِཅੑGBMTFQPTJUJWFSBUF FP N = FP FP + TN ӄੑͷͷΛཅੑͱஅׂͨ͠߹ !8
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ਅཅੑUSVFQPTJUJWFSBUF TP P = TP TP + FN ཅੑͷͷΛਖ਼͘͠ཅੑͱஅׂͨ͠߹ !9
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ద߹QSFDJTJPO TP TP + FP ཅੑͱஅͨ͠ͷͷ͏ͪຊʹཅੑͰ͋Δׂ߹ !10
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ࠶ݱSFDBMM TP P = TP TP + FN ཏੑʹؔ͢Δࢦඪ શཅੑͷ͏ͪݕग़Ͱ͖ͨͷͷׂ߹ !11
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ਖ਼֬BDDVSBDZ TP + TN P + N = TP + TN TP + FP + TN + FN ਖ਼ࣝ͘͠ผׂͨ͠߹ !12
ࠞಉߦྻ Q O ߦ Q ਅཅੑ 51 ِӄੑ '/ 151
'/ O ِཅੑ '1 ਅӄੑ 5' /'1 5/ ࣝผΫϥε ਅͷΫϥε ''NFBTVSF 2 1 precision + 1 recall ద߹ͱ࠶ݱͷௐฏۉ !13
ࠞಉߦྻ ِཅੑGBMTFQPTJUJWFSBUF FP N = FP FP + TN ӄੑͷͷΛཅੑͱஅׂͨ͠߹
ਅཅੑUSVFQPTJUJWFSBUF TP P = TP TP + FN ཅੑͷͷΛਖ਼͘͠ཅੑͱஅׂͨ͠߹ ద߹QSFDJTJPO TP TP + FP ཅੑͱஅͨ͠ͷͷ͏ͪ ຊʹཅੑͰ͋Δׂ߹ ࠶ݱSFDBMM TP P = TP TP + FN ཏੑʹؔ͢Δࢦඪ શཅੑͷ͏ͪݕग़Ͱ͖ͨͷͷׂ߹ ਖ਼֬BDDVSBDZ TP + TN P + N = TP + TN TP + FP + TN + FN ਖ਼ࣝ͘͠ผׂͨ͠߹ ''NFBTVSF 2 1 precision + 1 recall ద߹ͱ࠶ݱͷௐฏۉ !14
ࠞಉߦྻ ྫ ద߹ͱ࠶ݱͳͥτϨʔυΦϑͷؔʹ͋Δͷ͔ʁ ཏੑΛ্͛Α͏ͱཅੑͱड͚ೖΕΔͷΛ૿͢ͱ ِཅੑͱஅ͢Δͷ૿Ճ͠ɼ݁Ռͱͯ͠ద߹͕Լ͕ΔͨΊ ద߹QSFDJTJPO TP TP + FP
ཅੑͱஅͨ͠ͷͷ͏ͪ ຊʹཅੑͰ͋Δׂ߹ ࠶ݱSFDBMM TP P = TP TP + FN ཏੑʹؔ͢Δࢦඪ શཅੑͷ͏ͪݕग़Ͱ͖ͨͷͷׂ߹ !15
ِཅੑGBMTFQPTJUJWFSBUF FP N = FP FP + TN ӄੑͷͷΛཅੑͱஅׂͨ͠߹ ਅཅੑUSVFQPTJUJWFSBUF
TP P = TP TP + FN ཅੑͷͷΛਖ਼͘͠ཅੑͱஅׂͨ͠߹ ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ පؾͷਓ͔݈߁ͳਓͳͲͷαϯϓϧʹେ͖ͳภΓ͕͋Δ߹Ͱ ཅੑӄੑͷͷ͚ͩͰ࡞ΒΕ͍ͯΔͷͰɼͦΕͧΕӄੑཅੑͷӨڹΛड͚ͳ͍ 30$ۂઢ !16
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ِཅੑ ਅཅੑ # " $ ࣝผڥք Cp*
Cn* ཅੑͷ֬ͱӄੑͷ֬ ਅཅੑɿ ِཅੑɿ੨ ཅੑʢࠨʣଆͷ ֬ʹ͢Δ ୈछͷޡΓ ୈछͷޡΓͷ༨ࣄ !17
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ِཅੑ ਅཅੑ # " $ Cp* Cn*
ཅੑͷ֬ͱӄੑͷ֬ ࣝผڥք ཅੑʢࠨʣଆͷ ֬ʹ͢Δ !18 ਅཅੑɿ ِཅੑɿ੨ ୈछͷޡΓ ୈछͷޡΓͷ༨ࣄ
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ِཅੑ ਅཅੑ # " $ Cp* Cn*
ཅੑͷ֬ͱӄੑͷ֬ ࣝผڥք ཅੑʢࠨʣଆͷ ֬ʹ͢Δ !19 ਅཅੑɿ ِཅੑɿ੨ ୈछͷޡΓ ୈछͷޡΓͷ༨ࣄ
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣͱਅཅੑɾِཅੑ (0,0) (0.1,0.7) (1.0,1.0) ཅੑʢࠨʣଆͷ ֬ʹ͢Δ ʢԣɼॎʣʢِཅੑɼਅཅੑʣ !20 ਅཅੑɿ
ِཅੑɿ੨ ୈछͷޡΓ ୈछͷޡΓͷ༨ࣄ
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ΔE = 4 ΔE = 3 !21
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ΔE = 2 ΔE = 1 !22
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ΔE = 0 30$͔Βݴ͑Δ͜ͱԿ͔ʁ !23
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ཅੑͷ֬ͱӄੑͷ֬ͷॏͳΓ͕খ͍͞΄Ͳ 30$ͷԼ෦ͷ໘ੵ͕େ͖͘ͳ͍ͬͯΔ !24
30$ͷԼ෦ͷ໘ੵɿ"6$ "SFB6OEFSUIF$VSWF ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ᘳʹࣝผͰ͖Δɿ AUC = 1 શࣝ͘ผͰ͖ͳ͍ɿ AUC =
0.5 0.5 ≦ AUC ≦ 1.0 !25
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ "6$Λେ͖͘͢ΔͨΊʹ ྑ͍ੑͷ֬Λ࣋ͭಛྔͷΈ߹Θͤ !26
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣͱਅཅੑɾِཅੑ (0,0) (0.1,0.7) (1.0,1.0) ʢԣɼॎʣʢِཅੑɼਅཅੑʣ ͋͘·Ͱ ֬ͷੑೳධՁ Ͳͷʹ͢Εྑ͍ʁ 30$
!27
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ͋͘·Ͱ ֬ͷੑೳධՁ # " $ Ͳͷʹ͢Εྑ͍ʁ ͲͷࣝผڥքΛબྑ͍ʁ 30$ ཅੑͷ֬ͱӄੑͷ֬
!28
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ଛࣦ͕࠷খ͘͞ͳΔΑ͏ʹࣝผڥքΛܾΊΔ # " $ ࣝผڥք Cp* Cn* ِཅੑ ਅཅੑ
ཅੑͷྖҬʹ͓͚Δଛࣦ ଛࣦ ਅཅੑʹ༝དྷ͢Δଛࣦ ଛࣦ ِཅੑʹ༝དྷ͢Δଛࣦ r(C1 |x) = Σ2 k=1 L1k P(Ck |x) !29
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ཅੑͷྖҬʹ͓͚Δଛࣦ ଛࣦ ਅཅੑʹ༝དྷ͢Δଛࣦ ଛࣦ ِཅੑʹ༝དྷ͢Δଛࣦ r(C1 |x) = Σ2
k=1 L1k P(Ck |x) r(C1 |x) = L11 P(C1 |x) r(C1 |x) = L12 P(C2 |x) ਖ਼ࣝ͘͠ผͨ͠ͷʹଛࣦʁ - Λʹͯ͠د༩Λখ͘͢͞Δ r(C1 |x) = L12 P(C1 |x) ཅੑͷྖҬʹ͓͚Δ ࠷ऴతͳଛࣦ ଛࣦ͕࠷খ͘͞ͳΔΑ͏ʹࣝผڥքΛܾΊΔ !30
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ ӄੑྖҬʹ͓͚Δଛࣦಉ༷ʹॲཧ͢Δͱɼଛࣦ྆ऀͷظΛͱΔ͜ͱͰ r = E[r(x)] = ∫ R1 +R2 min[L12
P(C2 |x), L21 P(C1 |x)]p(x)dx = ∫ R1 L12 p(x|C2 )P(C2 )dx + ∫ R2 L21 p(x|C1 )P(C1 )dx ΫϥεΛཅੑʢQ ʣɼΫϥεΛӄੑʢO ʣͱ͢Ε r = ∫ p* Lp*n* p(x|Cn* )P(Cn* )dx + ∫ n* Ln*p* p(x|Cp* )P(Cp* )dx = Lp*n* P(Cn* )∫ p* p(x|Cn* )dx + Ln*p* P(Cp* )∫ n* p(x|Cp* )dx = Lp*n* P(Cn* )ϵ2 + Ln*p* P(Cp* )ϵ1 ୈछͷޡΓ ୈछͷޡΓ ଛࣦ͕࠷খ͘͞ͳΔΑ͏ʹࣝผڥքΛܾΊΔ !31
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ r = Lp*n* P(Cn* )ϵ2 + Ln*p* P(Cp* )ϵ1
30$ʹ͋ΔɼਅཅੑЏ ͱِཅੑЏ ͰࣜΛॻ͖͢ͱ࣍ࣜͷΑ͏ʹͳΔɽ 1 − ϵ1 = Lp*n* P(Cn* ) Ln*p* P(Cp* ) ϵ2 + (1 − r Ln*p* P(Cp* ) ) = αϵ2 + h(r) ͜ͷࣜ1 $Q ͱ1 $O ͓Αͼଛࣦ-Q O ͱ-O Q ʹΑͬͯЏ ͷ͖͕ܾ·Γɼ ยΛSͷؔͱͨ͠ઢͷํఔࣜͱଊ͑Δ͜ͱ͕Ͱ͖Δɽ ଛࣦ͕࠷খ͘͞ͳΔΑ͏ʹࣝผڥքΛܾΊΔ Ͱɼ༩͑ΒΕͨࣜͷதͰ࠷దͳࣜͲͷΑ͏ͳܗʹͳΔͩΖ͏͔ʁ ݅ҎԼͷ௨ΓͰ͋Δɽ min r = max h(r) ઢ͕30$ͱަΛ࣋ͭ ʜଛࣦ࠷খ ʜ͍࣋ͬͯΔσʔλͷ݅ͷൣғ !32
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ 1 − ϵ1 = αϵ2 + h(r) ଛࣦ͕࠷খ͘͞ͳΔΑ͏ʹࣝผڥքΛܾΊΔ min
r = max h(r) ઢ͕30$ͱަΛ࣋ͭ ʜଛࣦ࠷খ ʜ͍࣋ͬͯΔσʔλͷ݅ͷൣғ ݅ ยI S খଛࣦSେ ଛࣦ࠷খ͔ͭ30$ͱަΛ࣋ͭ (0.1,0.7) ͍͍ͩͨ ͘Β͍ʁ ਅཅੑͱِཅੑͷׂ߹͕ ͷʹͳΔΑ͏ʹࣝผڥքΛఆΊΔͱ ࠷ޡΓΛখͨࣝ͘͞͠ผ͕ՄೳʹͳΔ !33
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ 30$άϥϑ 30$Ϋϥεͷ͕Θ͔Βͳͯ͘ඳ͘͜ͱ͕Ͱ͖Δɽ ਅͷΫϥεͱσʔλͷείΞ Q
O ᮢͷείΞ4Ҏ্ͷείΞΛ࣋ͭσʔλΛQ ͱࣝผ͢Δɽ ͜ΕΛɼᮢΛมԽͤͯ͞܁Γସ͑͢ɽ !34
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ 30$άϥϑ Q O
30$Ϋϥεͷ͕Θ͔Βͳͯ͘ඳ͘͜ͱ͕Ͱ͖Δɽ ᮢ4 ਅཅੑ ِཅੑ 㱣 㱣 !35
ड৴ऀಈ࡞ಛੑۂઢʢ30$ʣ 30$άϥϑ Q O
30$Ϋϥεͷ͕Θ͔Βͳͯ͘ඳ͘͜ͱ͕Ͱ͖Δɽ !36
# " $ Cp* Cn* ِཅੑ ਅཅੑ ষ 30$ۂઢΛඳ͍ͨͱ͜ΖɼϥϯμϜࣝผΛද͢
ͷઢͷԼଆʹདྷͯ͠·ͬͨɽͲ͏͢Εྑ͍͔ɽ ্ਤͷਅཅੑͱِཅੑͷେ͖͕͞ٯస͍ͯ͠Δྫͱଊ͑ΒΕΔͷͰɼ ୯७ʹཅੑͱӄੑͷΫϥεΛٯస͢Ε͍͍ ͋Δ͍ɼ྆ํͷείΞʹϚΠφεΛ͔͚Δ͔ᮢͷεΩϟϯΛٯ͔Βߦ͏ͱ͔ !37
·ͱΊ ยI S খଛࣦSେ ྨͷධՁࠞಉߦྻ͔ΒಘΒΕΔ ͍͔ͭ͘ͷࢦඪͰߦ͑Δ ࠞಉߦྻΛ༩͑Δ֬ͷධՁ 30$ͷԼ෦໘ੵ "6$ ʹΑͬͯධՁ͢Δ
֬ͷ࠷ྑ͍ࣝผڥք 30$ͱϕΠζͷࣝผنଇͷ ଛࣦ͕࠷খʹͳΔΛબͿ͜ͱͰಘΒΕΔ 30$͕֬Θ͔Βͳͯ͘ ඳ͘͜ͱ͕Ͱ͖Δ !38
ଛࣦߦྻ ଛࣦʹؔ͢Δࣜʹग़ͯ͘Δ-ʹ͍ͭͯ r(Ci |x) = ΣK k=1 Lik P(Ck |x)
,ͷ࣌ɼS࠷؆୯ͳ-Λͬͯ࣍ͷΑ͏ʹॻ͖දΘͤΔɽ Lkj p(Ck |x) = (1 − Ikj )p(Ck |x) = {( 1 1 1 1) − ( 1 0 0 1)} ( p(C1 |x) p(C2 |x)) = ( 0 1 1 0) ( p(C1 |x) p(C2 |x)) = ( p(C2 |x) p(C1 |x)) ͜ͷதͰখ͍͞ํΛऔΔ࣌ҎԼͷΑ͏ʹॻ͚Δ min ( p(C2 |x) p(C1 |x)) !39