CS代考计算机代写 PowerPoint Presentation

PowerPoint Presentation

Diagnosis

Design & Creativity
Configuration
Diagnosis
Creativity
Design

Lesson Preview

Defining diagnosis

Data and hypothesis spaces

Mapping data to hypotheses

Two views of diagnosis

Patient:
A: Normal
B: High
C: Low
D: Normal
E: Normal
F: Normal
G: Normal
H: Low
Illnesses:
ο Alphaitis: Elevated A, Reduced C, Elevated F
ο Betatosis: Elevated B, Reduced C, Elevated E, Reduced H
ο Gammanoma: Elevated D, Elevated E, Elevated F
ο Deltacol: Elevated B, Reduced C
ο Epsicusus: Reduced H
ο Zetad: Elevated B, Reduced C, Reduced E, Reduced F
ο Etaemia: Elevated A, Reduced D, Reduced H
ο Thetadesis: Elevated B, Reduced C, Reduced H
ο Iotalgia: Elevated A, Reduced E, Elevated F, Elevated G
ο Kappacide: Reduced A, Reduced F, Reduced G
ο Lambdacrite: Reduced A, Reduced E, Reduced F, Reduced G
ο Mutension: Elevated A, Elevated G
What illness (or set of illnesses) would you use to diagnose this patient?

Diagnosis: To determine what is wrong with a malfunctioning device.

Diagnosis: To determine what is wrong with a malfunctioning device.

Image credit:
Tom Morris, https://commons.wikimedia.org/wiki/User:Tom_Morris
6

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract
Map

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract
Map
Refine

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract
Map
Refine

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #1: One data point, multiple hypotheses.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #2: One hypothesis, multiple sets of data.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #3: Multiple hypotheses, multiple sets of data.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #4: Mutually exclusive hypotheses.
But H3 and H6 are mutually exclusive.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #5: Interacting data points.
But D5 and D9 cancel each other out.

Rule
Cause
Effect

Rule
Cause
Effect
Deduction: Given the rule and the cause, deduce the effect.

Rule
Cause
Effect
Induction: Given a cause and an effect, induce a rule.

Rule
Cause
Effect
Abduction: Given a rule and an effect, abduce a cause.

Patient:
A: Normal
B: High
C: Low
D: Normal
E: Normal
F: Normal
G: Normal
H: Low
Illnesses:
ο Alphaitis: Elevated A, Reduced C, Elevated F
ο Betatosis: Elevated B, Reduced C, Elevated E, Reduced H
ο Gammanoma: Elevated D, Elevated E, Elevated F
ο Deltacol: Elevated B, Reduced C
ο Epsicusus: Reduced H
ο Zetad: Elevated B, Reduced C, Reduced E, Reduced F
ο Etaemia: Elevated A, Reduced D, Reduced H
ο Thetadesis: Elevated B, Reduced C, Reduced H
ο Iotalgia: Elevated A, Reduced E, Elevated F, Elevated G
ο Kappacide: Reduced A, Reduced F, Reduced G
ο Lambdacrite: Reduced A, Reduced E, Reduced F, Reduced G
What illness (or set of illnesses) would you use to diagnose this patient?

Criteria for Choosing Hypotheses
Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
1. Hypotheses must cover as much of the data as possible.

Criteria for Choosing Hypotheses
Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
1. Hypotheses must cover as much of the data as possible.

2. The smallest number of hypotheses ought to be used.

Criteria for Choosing Hypotheses
Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
1. Hypotheses must cover as much of the data as possible.

2. The smallest number of hypotheses ought to be used.

3. Some hypotheses may be more likely than others.

Patient:
A: Normal
B: High
C: Low
D: Normal
E: Normal
F: Low
G: Normal
H: Low
Illnesses:
ο Alphaitis: Elevated A, Reduced C, Elevated F
ο Betatosis: Elevated B, Reduced C, Elevated E, Reduced H
ο Gammanoma: Elevated D, Elevated E, Elevated F
ο Deltacol: Elevated B, Reduced C
ο Epsicusus: Reduced H
ο Zetad: Elevated B, Reduced C, Reduced E, Reduced F
ο Etaemia: Elevated A, Reduced D, Reduced H
ο Thetadesis: Elevated B, Reduced C, Reduced H
ο Iotalgia: Elevated A, Reduced E, Elevated F, Elevated G
ο Kappacide: Reduced A, Reduced F, Reduced G
ο Lambdacrite: Reduced A, Reduced E, Reduced F, Reduced G
ο Mutension: Elevated A, Elevated G
What illness (or set of illnesses) would you use to diagnose this patient?

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Abstract
Map
Refine

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Abstract
Map
Refine
Treatment Space
T1
T2
T3
T4
T5
T6
T7
T8
T9

TN

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Abstract
Map
Refine
Treatment Space
T1
T2
T3
T4
T5
T6
T7
T8
T9

TN

Chair Legs
count : 4
size : 10g
material : metal
cost : $4.00
Chair Seat
size : 100g
material : metal
cost : $10.00
Chair Arms
size : 0g
material : N/A
cost : $0.00
Chair Back
size : 20g
material : metal
cost : $2.00
Chair
mass : 160g
cost : $16
legs :
seat :
arms :
back :
What constraints dictated the design of this chair?

Image credit:
https://commons.wikimedia.org/wiki/File:Chair_4a.jpg

29

Assignment

How would you use diagnosis to design an agent that could answer Raven’s progressive matrices?

To recap…

Defining diagnosis

Process of diagnosis

Diagnosis as classification

Diagnosis as abduction

/docProps/thumbnail.jpeg

Posted in Uncategorized

Leave a Reply

Your email address will not be published. Required fields are marked *

CS代考计算机代写 PowerPoint Presentation

PowerPoint Presentation

Diagnosis

Design & Creativity
Configuration
Diagnosis
Creativity
Design

Lesson Preview

Defining diagnosis

Data and hypothesis spaces

Mapping data to hypotheses

Two views of diagnosis

Patient:
A: Normal
B: High
C: Low
D: Normal
E: Normal
F: Normal
G: Normal
H: Low
Illnesses:
ο Alphaitis: Elevated A, Reduced C, Elevated F
ο Betatosis: Elevated B, Reduced C, Elevated E, Reduced H
ο Gammanoma: Elevated D, Elevated E, Elevated F
ο Deltacol: Elevated B, Reduced C
ο Epsicusus: Reduced H
ο Zetad: Elevated B, Reduced C, Reduced E, Reduced F
ο Etaemia: Elevated A, Reduced D, Reduced H
ο Thetadesis: Elevated B, Reduced C, Reduced H
ο Iotalgia: Elevated A, Reduced E, Elevated F, Elevated G
ο Kappacide: Reduced A, Reduced F, Reduced G
ο Lambdacrite: Reduced A, Reduced E, Reduced F, Reduced G
ο Mutension: Elevated A, Elevated G
What illness (or set of illnesses) would you use to diagnose this patient?

Diagnosis: To determine what is wrong with a malfunctioning device.

Diagnosis: To determine what is wrong with a malfunctioning device.

Image credit:
Tom Morris, https://commons.wikimedia.org/wiki/User:Tom_Morris
6

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract
Map

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract
Map
Refine

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10
H11
H12

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9
D10
D11
D12

DN
Abstract
Map
Refine

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #1: One data point, multiple hypotheses.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #2: One hypothesis, multiple sets of data.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #3: Multiple hypotheses, multiple sets of data.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #4: Mutually exclusive hypotheses.
But H3 and H6 are mutually exclusive.

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Problem #5: Interacting data points.
But D5 and D9 cancel each other out.

Rule
Cause
Effect

Rule
Cause
Effect
Deduction: Given the rule and the cause, deduce the effect.

Rule
Cause
Effect
Induction: Given a cause and an effect, induce a rule.

Rule
Cause
Effect
Abduction: Given a rule and an effect, abduce a cause.

Patient:
A: Normal
B: High
C: Low
D: Normal
E: Normal
F: Normal
G: Normal
H: Low
Illnesses:
ο Alphaitis: Elevated A, Reduced C, Elevated F
ο Betatosis: Elevated B, Reduced C, Elevated E, Reduced H
ο Gammanoma: Elevated D, Elevated E, Elevated F
ο Deltacol: Elevated B, Reduced C
ο Epsicusus: Reduced H
ο Zetad: Elevated B, Reduced C, Reduced E, Reduced F
ο Etaemia: Elevated A, Reduced D, Reduced H
ο Thetadesis: Elevated B, Reduced C, Reduced H
ο Iotalgia: Elevated A, Reduced E, Elevated F, Elevated G
ο Kappacide: Reduced A, Reduced F, Reduced G
ο Lambdacrite: Reduced A, Reduced E, Reduced F, Reduced G
What illness (or set of illnesses) would you use to diagnose this patient?

Criteria for Choosing Hypotheses
Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
1. Hypotheses must cover as much of the data as possible.

Criteria for Choosing Hypotheses
Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
1. Hypotheses must cover as much of the data as possible.

2. The smallest number of hypotheses ought to be used.

Criteria for Choosing Hypotheses
Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
1. Hypotheses must cover as much of the data as possible.

2. The smallest number of hypotheses ought to be used.

3. Some hypotheses may be more likely than others.

Patient:
A: Normal
B: High
C: Low
D: Normal
E: Normal
F: Low
G: Normal
H: Low
Illnesses:
ο Alphaitis: Elevated A, Reduced C, Elevated F
ο Betatosis: Elevated B, Reduced C, Elevated E, Reduced H
ο Gammanoma: Elevated D, Elevated E, Elevated F
ο Deltacol: Elevated B, Reduced C
ο Epsicusus: Reduced H
ο Zetad: Elevated B, Reduced C, Reduced E, Reduced F
ο Etaemia: Elevated A, Reduced D, Reduced H
ο Thetadesis: Elevated B, Reduced C, Reduced H
ο Iotalgia: Elevated A, Reduced E, Elevated F, Elevated G
ο Kappacide: Reduced A, Reduced F, Reduced G
ο Lambdacrite: Reduced A, Reduced E, Reduced F, Reduced G
ο Mutension: Elevated A, Elevated G
What illness (or set of illnesses) would you use to diagnose this patient?

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Abstract
Map
Refine

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Abstract
Map
Refine
Treatment Space
T1
T2
T3
T4
T5
T6
T7
T8
T9

TN

Hypothesis Space
H1
H2
H3
H4
H5
H6
H7
H8
H9

HN
Data Space
D1
D2
D3
D4
D5
D6
D7
D8
D9

DN
Abstract
Map
Refine
Treatment Space
T1
T2
T3
T4
T5
T6
T7
T8
T9

TN

Chair Legs
count : 4
size : 10g
material : metal
cost : $4.00
Chair Seat
size : 100g
material : metal
cost : $10.00
Chair Arms
size : 0g
material : N/A
cost : $0.00
Chair Back
size : 20g
material : metal
cost : $2.00
Chair
mass : 160g
cost : $16
legs :
seat :
arms :
back :
What constraints dictated the design of this chair?

Image credit:
https://commons.wikimedia.org/wiki/File:Chair_4a.jpg

29

Assignment

How would you use diagnosis to design an agent that could answer Raven’s progressive matrices?

To recap…

Defining diagnosis

Process of diagnosis

Diagnosis as classification

Diagnosis as abduction

/docProps/thumbnail.jpeg

Posted in Uncategorized

Leave a Reply

Your email address will not be published. Required fields are marked *