1.2 Expert Systems
How rules-based systems can be used for binary classification
Human decision making
How do humans make decisions?
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Dengue
headache
cold cough
vomiting
fever
skin rash
Human decision making
How do humans make decisions from past experiences?
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fever
headache
cold cough
vomiting
Rash
Inputs
Output
Human decision making
How do humans make decisions from past experiences?
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fever
headache
cold cough
vomiting
Rash
inputs
output
1 | 0 | 0 | 0 | 0 |
---|---|---|---|---|
1 | 0 | 0 | 1 | 0 |
1 | 1 | 1 | 0 | 1 |
1 | 0 | 1 | 1 | 0 |
0 |
---|
0 |
1 |
0 |
0
1
Human decision making
Is this applicable in multiple domains ?
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LBW out
Impact
Height
no ball
shot attempted
Pitching in line
Inputs
Output
Human decision making
Is this applicable in multiple domains ?
(c) One Fourth Labs
LBW out
Impact
Height
no ball
shot attempted
Pitching in line
Inputs
Output
1 | 1 | 0 | 1 | 0 |
---|---|---|---|---|
1 | 1 | 1 | 0 | 0 |
1 | 1 | 1 | 0 | 1 |
1 | 0 | 1 | 1 | 0 |
0 |
---|
1 |
1 |
0 |
0
1
Features and Rules
What is the semantics of decision making?
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Output
Inputs
headache
cold cough
vomiting
fever
skin rash
Fever
Rash
Cold
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if HIGH_FEVER and COLD:
return no_dengue
elif HIGH_FEVER and VOMITING and not RASH:
return no_dengue
elif HIGH_FEVER and VOMITING and RASH:
return dengue
Output
Inputs
Fever
Rash
Cold
Expert Systems
How do we outsource this to a machine?
headache
cold cough
vomiting
fever
skin rash
Use-cases
Where have expert systems been used - past and recent applications
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(1990)
(1990)
(1965)
(1995)
(2018)
Hanane et. al., Expert Systems, May 2018.
Limitations
Do we need to look beyond expert systems?
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Task of hiring someone for a job
10th marks
12th marks
graduate
post graduate
projects
if 10th>90 and 12>90 and GRADUATE:
return hired
elif 10th>80 and 12th>80 and POST_GRADUATE:
return hired
elif 10th<70 and 12th<70:
return not_hired
10th
12th
graduate
Output
YES / NO
Inputs
Limitations
Do we need to look beyond expert systems?
(c) One Fourth Labs
Task of hiring someone for a job - involving many factors
10th marks
if 10th>90 and 12>90 and GRADUATE:
return hired
elif 10th>80 and 12th>80 and POST_GRADUATE:
return hired
elif 10th<70 and 12th<70:
return not_hired
10th
12th
graduate
12th marks
graduate
post graduate
projects
awards
.....
10th marks | 12th marks | graduate | post graduate | projects | ........... | awards |
---|---|---|---|---|---|---|
92 | 82 | yes | yes | 3 | ........... | 2 |
83 | 75.2 | yes | no | 1 | ........... | 0 |
75 | 70 | no | no | 0 | ........... | 1 |
96 | 95 | yes | yes | 5 | ........... | 4 |
90 | 89 | yes | yes | 2 | ........... | 1 |
78 | 82 | yes | no | 0 | ........... | 0 |
86 | 88 | yes | no | 1 | ........... | 1 |
Lots of data to make sense from
Output
YES / NO
Limitations
Do we need to look beyond expert systems?
10th marks | 12th marks | graduate | post graduate | projects | ........... | awards |
---|---|---|---|---|---|---|
92 | 82 | yes | yes | 3 | ........... | 2 |
83 | 75.2 | yes | no | 1 | ........... | 0 |
75 | 70 | no | no | 0 | ........... | 1 |
96 | 95 | yes | yes | 5 | ........... | 4 |
90 | 89 | yes | yes | 2 | ........... | 1 |
78 | 82 | yes | no | 0 | ........... | 0 |
86 | 88 | yes | no | 1 | ........... | 1 |
if 10th>90 and 12>90 and GRADUATE:
return hired
elif 10th>80 and 12th>80 and POST_GRADUATE:
return hired
elif 10th<70 and 12th<70:
return not_hired
elif awards>2 and GRADUATE:
return hired
elif not POST_GRADUATE and publications>1:
return hired
elif projects>10 and publications>2:
return hired
elif competitions>3 and publications>3:
return hired
elif awards>5:
return hired
elif GRADUATE and not POST_GRADUATE and awards>5:
return hired
The rules can be very complex
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Limitations
Do we need to look beyond expert systems?
The rules can sometimes be unknown:
- task of predicting Ebola
Output
high fever
headache
sore throat
weakness
nausea
?
?
YES / NO
Inputs
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Limitations
Do we need to look beyond expert systems?
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The rules can be sometimes inexpressible
10th marks
12th marks
graduate
post graduate
projects
Output
YES / NO
Inputs
?
I saw
(c) One Fourth Labs
Say Hi to Machine Learning
How to move from writing rules to learning rules?
10th marks | 12th marks | graduate | post graduate | projects | ........... | awards | HIRED |
---|---|---|---|---|---|---|---|
92 | 82 | yes | yes | 3 | ........... | 2 | yes |
83 | 75.2 | yes | no | 1 | ........... | 0 | yes |
75 | 70 | no | no | 0 | ........... | 1 | no |
96 | 95 | yes | yes | 5 | ........... | 4 | yes |
90 | 89 | yes | yes | 2 | ........... | 1 | yes |
78 | 82 | yes | no | 0 | ........... | 0 | no |
86 | 88 | yes | no | 1 | ........... | 1 | no |
def f(x):
if 10th>90 and 12>90 and GRADUATE:
return hired
elif 10th>80 and 12th>80 and POST_GRADUATE:
return hired
elif 10th<70 and 12th<70:
return not_hired
10th
12th
graduate
Output
YES / NO
def f(x):
i=0
max_epochs=100
w = rand()
while(i<max_epochs):
dw = grad(w,w*x)
w = w - lr*dx
i += 1
return w*x
Data, Democratization, Devices
Why has Machine Learning been so successful ?
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In most applications we have limited intuition but infinite data
ML engines have been standardised and democratised
Show many gears and then say it is about matching a gear to your data ?
Different roles in the ML world
How this relates to you ?
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Show the gears and data on LHS
Show a pyramid:
- Most problems about curating data
- Some problems about optimizing existing algorithms
- Research on new algorithms
Takeaway
How do we contrast expert systems from machine learning?
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Expert systems are useful when we can specify rules - some use cases still exist
But primarily focus is on machine learning, where rules are discovered by learning from data
// show a collage of respective applications
// very few icons for expert systems
// many many icons for ML
Text
Copy of Copy of 1.2 Expert Systems
By suman banerjee
Copy of Copy of 1.2 Expert Systems
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