tr rt s t - - PowerPoint PPT Presentation

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❆✉t❤♦r ❱❡r✐✜❝❛t✐♦♥✿ ❇❛s✐❝ ❙t❛❝❦❡❞ ●❡♥❡r❛❧✐③❛t✐♦♥ ❆♣♣❧✐❡❞ ❚♦ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs

❊r✇❛♥ ▼♦r❡❛✉✱ ❆r✉♥ ❏❛②❛♣❛❧✱ ●❡r❛r❞ ▲②♥❝❤ ❛♥❞ ❈❛r❧ ❱♦❣❡❧

❈◆●▲ ✫ ❚r✐♥✐t② ❈♦❧❧❡❣❡ ❉✉❜❧✐♥ ♠♦r❡❛✉❡❅❝s✳t❝❞✳✐❡✱ ❥❛②❛♣❛❧❛❅❝s✳t❝❞✳✐❡✱ ❣❡r❛r❞✳❧②♥❝❤❅✉❝❞✳✐❡✱ ✈♦❣❡❧❅❝s✳t❝❞✳✐❡ ❚❤✐s r❡s❡❛r❝❤ ✐s s✉♣♣♦rt❡❞ ❜② ❙❝✐❡♥❝❡ ❋♦✉♥❞❛t✐♦♥ ■r❡❧❛♥❞ ✭●r❛♥t ✶✷✴❈❊✴■✷✷✻✼✮ ❛s ♣❛rt ♦❢ t❤❡ ❈❡♥tr❡ ❢♦r ◆❡①t ●❡♥❡r❛t✐♦♥ ▲♦❝❛❧✐s❛t✐♦♥ ✭✇✇✇✳❝♥❣❧✳✐❡✮ ❢✉♥❞✐♥❣ ❛t ❚r✐♥✐t② ❈♦❧❧❡❣❡✱ ❯♥✐✈❡rs✐t② ♦❢ ❉✉❜❧✐♥✳

P❆◆ ✷✵✶✺

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✶✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❆♣♣r♦❛❝❤

◮ ❘❡❣r❡ss✐♦♥ ♣r♦❜❧❡♠ ✭❛t t❤❡ ❞❛t❛s❡t ❧❡✈❡❧✮

◮ ♦♥❡ ✐♥st❛♥❝❡ ❂ ♦♥❡ ♣r♦❜❧❡♠ ✭❦♥♦✇♥ ❞♦❝s ✰ ✉♥❦♥♦✇♥ ❞♦❝✮ ◮ ♦♣t✐♠✐③❡ ❆❯❈ × ❝❅✶

◮ ❈♦♠❜✐♥✐♥❣ ♠✉❧t✐♣❧❡ ❧❡❛r♥❡rs ◮ ●❡♥❡t✐❝ ❛❧❣♦r✐t❤♠ ✉s❡❞ t♦✿

◮ tr❛✐♥ t❤❡ ✐♥❞✐✈✐❞✉❛❧ ❧❡❛r♥❡rs✱ ◮ tr❛✐♥ t❤❡ ♠❡t❛✲♠♦❞❡❧✳ ❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✷✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

◮ ❊①♣❡r✐❡♥❝❡ ❢r♦♠ P❆◆✬✷✵✶✹✿

◮ ●❡♥❡t✐❝ ❛❧❣♦r✐t❤♠✿ t❡♥❞s t♦ ♦✈❡r✜t ◮ ❚✇♦ ❛♣♣r♦❛❝❤❡s✿ ◮ ❋✐♥❡✲❣r❛✐♥❡❞✿ ♠❛♥② ♣❛r❛♠❡t❡rs t♦ ♠❛①✐♠✐③❡ ♣❡r❢♦r♠❛♥❝❡ ◮ ❘♦❜✉st✿ ❜❛s✐❝ ❛♣♣r♦❛❝❤ t♦ ❛✈♦✐❞ ♦✈❡r✜tt✐♥❣

→ str❛t❡❣② ❝❤♦s❡♥ ♠❛♥✉❛❧❧② ❜② ❞❛t❛s❡t

◮ ❘❡s✉❧ts ♦❜t❛✐♥❡❞ ❜② t❤❡ ♦r❣❛♥✐③❡rs ♠❡t❛✲♠♦❞❡❧✿

• Fig. 1. ROC graphs of the best performing submissions and their convex hull, the baseline

method, and the meta-classifier. 0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1 TPR FPR Frery et al. Khonji & Iraqi Mayor et al. Moreau et al. Baseline Meta-Classifier Convex Hull

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✸✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❙tr❛t❡❣✐❡s

✶✳ ❋✐♥❡✲❣r❛✐♥❡❞ str❛t❡❣②✿ ♠❛♥② ♣❛r❛♠❡t❡rs✱ ♠❛①✐♠✐③❡ ♣❡r❢♦r♠❛♥❝❡ ✷✳ ❘♦❜✉st str❛t❡❣②✿ ❜❛s✐❝ ❛♣♣r♦❛❝❤✱ s❛❢❡r ✸✳ ●❡♥❡r❛❧ ■♠♣♦st♦r

◮ ■❞❡❛✿ ♠❡t❛✲❝♦♠♣❛r✐s♦♥ ❛❣❛✐♥st t❤✐r❞✲♣❛rt② ❞♦❝✉♠❡♥ts ◮ ❯s❡❞ ❜② ❜❡st s②st❡♠ ❛t P❆◆✬✶✹

✹✳ ❚♦♣✐❝ ♠♦❞❡❧❧✐♥❣

◮ ▼♦❞✐✜❡❞ ❢♦r st②❧❡ ❞✐st✐♥❝t✐✈❡♥❡ss ◮ ●♦❛❧ ❂ ❈♦♠♣❧❡♠❡♥t❛r✐t②

✺✳ ❯♥✐✈❡rs✉♠ ■♥❢❡r❡♥❝❡

◮ ❇♦♦tstr❛♣♣✐♥❣ ♠❡t❤♦❞ ◮ ❍♦♠♦❣❡♥✐t② ♦❢ ❞♦❝✉♠❡♥ts s♥✐♣♣❡ts ♠✐①❡❞ t♦❣❡t❤❡r ❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✹✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❈♦♥✜❣✉r❛t✐♦♥s

◮ ❘❡♣r❡s❡♥t✐♥❣ ❞✐st✐♥❝t s❡t ♦❢ ♣❛r❛♠❡t❡rs ✐♥ ❛♥ ❤♦♠♦❣❡♥❡♦✉s ✇❛② ◮ ❙❡t ♦❢ ❦❡②✲✈❛❧✉❡ ♣❛✐rs✿ ❈ = {♣✶ → ✈✶, . . . , ♣♥ → ✈♥} ◮ ❉❡s❝r✐❜❡ t❤❡ ♠❡t❛✲♣❛r❛♠❡t❡rs ♦❢ ❛ str❛t❡❣②

◮ ■♥ tr❛✐♥✐♥❣ ♠♦❞❡✱ ❛ ❝♦♥✜❣✉r❛t✐♦♥ ❈ ❛♥❞ ❛ s❡t ♦❢ ✐♥st❛♥❝❡s

✭♣r♦❜❧❡♠s✮ ❙ ❞❡✜♥❡ ❛ ♠♦❞❡❧ ▼ ✐♥ ❛ ✉♥✐q✉❡ ✇❛②✿ ❢tr❛✐♥(❈, ❙) = ▼

◮ ■♥ t❡st✐♥❣ ♠♦❞❡✱ ❛ ❝♦♥✜❣✉r❛t✐♦♥ ❈✱ ❛ ♠♦❞❡❧ ▼ ❛♥❞ ❛♥

✐♥st❛♥❝❡ s ❞❡✜♥❡ ❛ ✉♥✐q✉❡ ♣r❡❞✐❝t✐♦♥✿ ❢t❡st(❈, ▼, s) = ♣

◮ ❙♣❡❝✐✜❝ s❡t ♦❢ ♣❛r❛♠❡t❡rs ❢♦r ❡❛❝❤ str❛t❡❣② ◮ ❱❡r② ❧❛r❣❡ s♣❛❝❡ ♦❢ ♣♦ss✐❜❧❡ ❝♦♥✜❣s

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✺✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❈♦♠♠♦♥ t♦ ❛❧❧ str❛t❡❣✐❡s

◮ ▲♦✇✲❧❡✈❡❧ ❢❡❛t✉r❡s✿ ✈❛r✐♦✉s ❦✐♥❞s ♦❢ ♥✲❣r❛♠s

◮ ✇♦r❞s✱ ❧❡tt❡rs✱ P❖❙ t❛❣s✱ s❦✐♣✲❣r❛♠s✳✳✳

◮ ❖✉t♣✉t ♦❢ t❤❡ str❛t❡❣②✿ ❛ s❡t ♦❢ ✐♥❞✐❝❛t♦rs ✭❤✐❣❤✲❧❡✈❡❧ ❢❡❛t✉r❡s✮ ◮ ❘❡❣r❡ss✐♦♥ ❛❧❣♦r✐t❤♠ → s❝♦r❡ ✐♥ [✵, ✶]

◮ ❙❱▼ r❡❣r❡ss✐♦♥✱ ❉❡❝✐s✐♦♥ tr❡❡s r❡❣r❡ss✐♦♥

◮ ❖♣t✐♦♥❛❧✿ ❝❧❛ss✐✜❝❛t✐♦♥ t♦ tr② t♦ ❞❡t❡❝t ❛♠❜✐❣✉♦✉s ❝❛s❡s

◮ ❯s❡s ✐♥❞✐❝❛t♦rs ✰ ♣r❡❞✐❝t❡❞ s❝♦r❡ ◮ ❖♣t✐♠✐③❡ ❈❅✺ s❝♦r❡ ❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✻✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

• ❡♥❡t✐❝ ❆❧❣♦r✐t❤♠

◮ ❆ ♠✉❧t✐✲❝♦♥✜❣✉r❛t✐♦♥ ❛ss♦❝✐❛t❡s ♠✉❧t✐♣❧❡ ✈❛❧✉❡s t♦ ♦♥❡

♣❛r❛♠❡t❡r✿ ▼❈ =

• ♣✶ → {✈✶

✶ , . . . , ✈✶ ♠✶}, . . . , ♣♥ → {✈♥ ✶ , . . . , ✈♥ ♠♥}

• ◮ ✶ ❝♦♥✜❣✉r❛t✐♦♥ ❂ ✶ ✏✐♥❞✐✈✐❞✉❛❧✑

◮ ▼✉❧t✐✲❝♦♥✜❣✉r❛t✐♦♥ ❂ s♣❛❝❡ ♦❢ ❛❧❧ ❝♦♠❜✐♥❛t✐♦♥s ❂ ✐♥♣✉t ◮ ❇❛s✐❝ ❣❡♥❡t✐❝ ♣r♦❝❡ss✿

◮ ✜rst ❣❡♥❡r❛t✐♦♥ ✐♥✐t✐❛❧✐③❡❞ r❛♥❞♦♠❧② ◮ ❚❤❡♥ s❡❧❡❝t✐♦♥ ❜❛s❡❞ ♦♥ ♣r❡✈✐♦✉s ❣❡♥❡r❛t✐♦♥ ♣❡r❢♦r♠❛♥❝❡ ◮ P♦ss✐❜✐❧✐t② ♦❢ ♠✉t❛t✐♦♥✳

◮ ❙❡❧❡❝ts ❛ s✉❜s❡t ♦❢ ♦♣t✐♠❛❧ ❝♦♥✜❣✉r❛t✐♦♥s ❢♦r ❡❛❝❤ str❛t❡❣②

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✼✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❆r❝❤✐t❡❝t✉r❡

strategy multi-config N best configs strategy training set random configs evaluation + genetic selection selected configs evaluation + genetic selection

Strategy learning process

Generation 1 Generation 2 stop criterion: no more perf improvement strategy 1 N configs strategy 2 N configs strategy 3 N configs strategy 4 N configs strategy 5 N configs meta multi-config:

• which strategy

predictions

• how to combine

the predictions meta training set random configs evaluation + genetic selection selected configs evaluation + genetic selection

Meta learning process

Generation 1 Generation 2 stop criterion: no more perf improvement meta-model

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✽✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

▼▲ ❙❡tt✐♥❣

❘✐s❦ ❂ ♦✈❡r✜tt✐♥❣

◮ ●❡♥❡t✐❝ ♣r♦❝❡ss✿ ✐♥♥❡r ❦✲❢♦❧❞ ❈❱

◮ ◆❡✇ ❦✲♣❛rt✐t✐♦♥✐♥❣ ❛t ❡✈❡r② ❣❡♥❡r❛t✐♦♥

◮ ❈❤❛✐♥❡❞ s❡q✉❡♥❝❡s ✇✐t❤ ❦ ✐♥❝r❡❛s❡❞ ◮ ❋✐♥❛❧ ✶✵ × ✷ ❈❱

◮ ❈♦♥tr♦❧ t❤❡ ✐♥✢✉❡♥❝❡ ♦❢ ❦✲♣❛rt✐t✐♦♥✐♥❣

❍②❜r✐❞ s❡t✉♣

◮ ❚r❛✐♥✐♥❣ s❡t s♣❧✐t ✐♥t♦✿

◮ ❙tr❛t❡❣② tr❛✐♥✐♥❣✿ ✺✵✪ ✐♥st❛♥❝❡s ◮ ▼❡t❛✲st❛❣❡ tr❛✐♥✐♥❣✿ ✷✺✪ ◮ ▼❡t❛ t❡st s❡t✿ ✷✺✪

✰ ❋✐♥❛❧ ❡✈❛❧ ✇✐t❤ ❜❛❣❣✐♥❣ ✰ ❖✈❡r❛❧❧ ✷✲❢♦❧❞ ❈❱

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✾✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❘❡s✉❧ts

❉❛t❛s❡t

▼❡t❛ t❡st s❡t ❋✉❧❧ tr❛✐♥✐♥❣ s❡t ❚❡st s❡t

♣❡r❢✳ r❛♥❦ ❉✉t❝❤ ✵✳✼✶✵ ✵✳✼✷✷ ✵✳✻✸✺ ✶st ❊♥❣❧✐s❤ ✵✳✹✵✺ ✵✳✹✷✶ ✵✳✹✺✸ ✻t❤

• r❡❡❦

✵✳✻✺✻ ✵✳✼✻✶ ✵✳✻✾✸ ✷♥❞ ❙♣❛♥✐s❤ ✵✳✾✺✵ ✵✳✾✺✷ ✵✳✻✻✶ ✹t❤ ▼❛❝r♦✲❛✈❡r❛❣❡ ✵✳✻✶✵ ✷♥❞

◮ ■♥✢✉❡♥❝❡ ♦❢ t❤❡ s✐③❡ ♦❢ t❤❡ s❛♠♣❧❡

◮ ❊♥❣❧✐s❤✿ ♦♥❧② ♦♥❡ ❦♥♦✇♥ ❞♦❝ ❜② ❝❛s❡ ◮ ❙♣❛♥✐s❤✿ ❢♦✉r ❦♥♦✇♥ ❞♦❝s ❜② ❝❛s❡

◮ ❙✐♠✐❧❛r ♣❡r❢ ♦♥ tr❛✐♥✐♥❣ ❛♥❞ t❡st s❡t

◮ ♥♦ ♦✈❡r✜tt✐♥❣ ✭❡①❝❡♣t ✇✐t❤ ❙♣❛♥✐s❤✮ ❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✶✵✴✶✶

■♥tr♦❞✉❝t✐♦♥ ▼♦t✐✈❛t✐♦♥s ■♥❞✐✈✐❞✉❛❧ ▲❡❛r♥❡rs

• ❡♥❡t✐❝ ❛❧❣♦r✐t❤♠

■♠♣❧❡♠❡♥t❛t✐♦♥ ❘❡s✉❧ts

❈♦♥❝❧✉s✐♦♥ ❛♥❞ ❢✉t✉r❡ ✇♦r❦

◮ ❈♦♠❜✐♥✐♥❣ ❤❡t❡r♦❣❡♦✉s ❧❡❛r♥❡rs ✇♦r❦s ✇❡❧❧ ◮ ❲♦r❦s ❜❡tt❡r ✇✐t❤ ♠♦r❡ ✐♥❢♦r♠❛t✐♦♥ ◮ ❙❡❧❡❝t✐♥❣ ❧❡❛r♥❡rs ❜❛s❡❞ ♦♥ ❞✐✈❡rs✐t②❄ ◮ ■♥ ♣r♦❣r❡ss✿ ♠❛❦✐♥❣ t❤❡ ❝♦❞❡ ❛✈❛✐❧❛❜❧❡

❈♦♠❜✐♥❡❞ Pr❡❞✐❝t✐♦♥s ❢r♦♠ ❛ ❙❡t ♦❢ ❍❡t❡r♦❣❡♥❡♦✉s ▲❡❛r♥❡rs ✲ ❈◆●▲ ✫ ❚❈❉ ✶✶✴✶✶