Model Interpretation Machine Learning for Data Science 1 EE - - PowerPoint PPT Presentation

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Model Interpretation Machine Learning for Data Science 1 EE - - PowerPoint PPT Presentation

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exploinobility as interpretobility Model Interpretation Machine Learning for Data Science 1 EE ploinoble At the extend to wash and wise interpretobility o are be obscured within effect a 1 system are ableto predict the extend to which we

slide-1
SLIDE 1

Model Interpretation

Machine Learning for Data Science 1

exploinobility

as interpretobility

EEploinoble At

interpretobility

  • the extend to wash

wise

and

effect

are beobscuredwithin

a

1

system

theextend to which

we

are ableto predict

who t is going tohopperuponderageofthemput

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SLIDE 2

the degree to which

bum

co predictthe

model's

result

exploiaobility

extend to

which the

uterine

mechanics ofthe system

can be explained inhumoutermst

background

www.t

Knowledge

example

chemical experiment

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Harpeth

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5

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expel understandtenduenisty

slide-3
SLIDE 3

bogey

transparency

  • r the lookof

corporateself interest

absence of governance

and accountability

ML gets two loud

in biggest businesses

and polite

Cowbridge Anolytice

crime justice

medicine

health core

curvy

  • uter

vision

acccouthility

transposing

trust

understand thewooliges ofthe model

slide-4
SLIDE 4
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SLIDE 5

Mistakes

slide-6
SLIDE 6
slide-7
SLIDE 7

e

in

slide-8
SLIDE 8

F

slide-9
SLIDE 9

block

box

models

a function too complicated

for

a

humour to comprehend

a propriotory fanctoon

ranking of the web pogies

psychotryapnhibited

level

a

we

slide-10
SLIDE 10

accuracy

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poor

interpretable perfomeone

fooled

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SLIDE 11

Joi ruess

predict

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bio seed

and

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wot disaicniceote demographic mae J

primes

exclude g privateTufo

to cetology

reliability

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tier

trust

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SLIDE 12

sowe.to

y

Model specific

tegnostic

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deterpretotioncoptility

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does not depend

the

ANN

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SLIDE 13

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humour

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evolution layperson

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slide-14
SLIDE 14

Propertiesof methodsfor interpretation

expresie power

trous lucency

portability

compexexity

repertiesofmethods

for individual

explanations

x

z

accuracy

fidelity

consistency

stolility

comprehensibility

certainty

degreegireportoace

novelty 3 break ku

slide-15
SLIDE 15

LIME

a

to Col Surrogate

block

box

portofthe futurespace

load interpretable

beodee agnostic explotrofias

Expire in individual predictions

1

select

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iustou ee

l Ga e ofinterest

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and getpredictions

3 bfaigight

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weig

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t outcome

BBM interpretable model tree

liu reg bag Reg

NBC

slide-16
SLIDE 16

g

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SLIDE 17
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SLIDE 18

A

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i

slide-19
SLIDE 19

y

f

Tes

X

slide-20
SLIDE 20

i

too

slide-21
SLIDE 21

Line

  • _O
slide-22
SLIDE 22

Shepley Values

effectsof the

freebase values

  • n

a

  • utcome of

a model

each future

as

a player

in

a game

distribute the prey out

ang

the future

coalitions

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e subsetof players to

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worthof coolietiers

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SLIDE 23

i

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144

14

150 3

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slide-24
SLIDE 24

Algorithm

approximate 01 Cx

the importance

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i th future's value forinstance x

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model f

toiled

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sweats

for

1 to IL

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g i G 1k

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SLIDE 25

A

th

a proximateOli j

globalimportance

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th Jobevolney for

a modelf

i j

  • for K

L to be

i

i j

di j

t f E

f g

Oli j

e di j l k

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SLIDE 26
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SLIDE 27

SHAP

e

housing date

slide-28
SLIDE 28

O

O

O

a

t

slide-29
SLIDE 29

GlobolsigoE

si

I

no

Returpretobee

f

Crees

slide-30
SLIDE 30
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SLIDE 31

nfihplEZh

ti.ws aJt lsieeG

error

complexity

ba fie

  • iout iiloglttexpfF

Ebjxzj

tdT.gl bj to

RiskSLlM

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SLIDE 32

a

i

s't

slide-33
SLIDE 33
slide-34
SLIDE 34
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SLIDE 35

lb

Hi

is I

I

9

  • O

x

slide-36
SLIDE 36

Legisiegression

I

I

e

xE

log

Wot

were

twnxu.bg

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s

1

53

lookup for

homognopfous

pcs

slide-37
SLIDE 37

KoHou R Sandino

i

in

I

r

ni

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SLIDE 38
slide-39
SLIDE 39
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SLIDE 40

I beg

gepfE.de

p yfet.tostxT

slide-41
SLIDE 41

OF

slide-42
SLIDE 42

I

slide-43
SLIDE 43

I

prototyers

O

O

O

O

slide-44
SLIDE 44

Dudincoucludies

block box

models

  • ne

cent necessary

needed for

accurate predictions

focus of future engineers

were effort

sofety

R trust

MLurodes

slide-45
SLIDE 45