Transcript Слайд 1 - International MCDM Society

A Role of Dialogue Strategy in
Multiattribute Classification Performance
Eugenia Furems
Institute for System Analysis
of Russian Academy of Sciences
[email protected]
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
A Role of Dialogue Strategy in Multiattribute
Classification Performance
Outline
1.
2.
3.
4.
5.
6.
7.
Verbal Decision Analysis (VAR) – principles & methods
Knowledge-based multiattribute classification
Cognitive difficulties & their avoidance
VDA-based method for Nominal-Ordinal Classification
(NORCLASS)
Advantages and Disadvantages of NORCLASS
Modification of NORCLASS dialogue and its
effectiveness
Conclusion
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Verbal Decision Analysis – Principles
•
•
Human (DM’s, expert’s) judgements (in verbal
or, in other words, qualitative form) - the
primary source of information for decision
making problems solving
Processing such information without any
quantitative conversion, so that any resulting
conclusion is both transparent and wellexplainable to the DM/expert .
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Verbal Decision Analysis - Methods
Problems
Multicriteria
Choice Problem
ZAPROS
Classification problem
UniComBos
Preference-based
multicriteria
classification
ORCLASS,
DIFCLASS, CLARA
NORCLASS
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Knowledge-based
multiattribute
classification
STEPCLASS
Knowledge-based Multiattribute
Classification
Assigning the given objects, described with
the values upon multiple attributes, to the
classes* (from their pre-defined set)
according to the expert knowledge.
* Class - a set of objects in respect of which the
expert makes the same (classification, diagnostic,
etc.) decision.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Cognitive Problems & Their Avoidance
“An Expert knows more than he/she is able to say”
Although an expert would be able to list some classification
rules directly, most certainly these rules would be
applicable to the typical objects only. So, the set of such
rules would be incomplete both in regard of the domain
coverage, and in relation to his/her knowledge.
Cause: an expert does not formulate the rules in his/her
daily activity, but he/she applies them while analyzing the
real-world objects.
Way out: Simulating objects to be classified and
presenting them to the expert for analysis and
classification.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Prerequisites for VDA-based
Multiattribute Classification Methods
1. Completeness of the expert-specified rules,
that allow to classify each object from the set
of all hypothetically possible objects in the
given application domain described by the
values of the expert-specified attributes.
2. Consistency of rules: Any number of rules
may be specified for an object; however, all
of these rules have to assign it to the same
class
3. Avoidance of exhaustive search while the
expert’s classification rules eliciting.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
VDA-based method NORCLASS
NORCLASS is designed for NOminal-ORdinal
CLASSification, where classes correspond to
non-orderable decisions, but the expert is able
to order the values of each and every attribute
according to their inherence in (typicality to) each
such class independently of the values of other
attributes.
:
_________________________________________________________________________________
Larichev O, Moshkovich H, Furems E et al (1991) Knowledge Acquisition for the Construction of the
Full and Contradiction Free Knowledge Bases. Iec ProGAMMA, Groningen, The Netherlands.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Example
Myocardial
Infarction
Stenocardia
The retrosternal pain
1
2
The pain left to sternum
3
1
The pain under the left scapula
2
3
Localization of Pain
1 – the most inherent, 3 – the least inherent
MCDM 2011, Jyvaskyla, Finland,
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Formal Statement of Multiattribute
Classification Problem in NORCLASS
It is given:


− the names of classes pre-defined by the
expert;
C  Cl l  1, L
Q  Q1 , Q2 ,...QM

Km  km1, km2 ,...,kmnm
A=K1xK2x…xKM


− the names of attributes, values of which
describe the features of objects of the
given Application Domain (AD)
− the values (the scale) of the m-th attribute
− the set of M-attribute descriptions of all
hypothetically possible objects of the AD;
ai  ai1 , ai 2 ,...,aiM , aim  Km , m  1, M
It is required: Assign the objects from A to classes from C on the
basis of the expert’s knowledge so that the resulting classification is
both complete (up to the expert’s knowledge) and consistent
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Ordering by Inherence
R  Km  Km
l
m
−reflexive and transitive binary
relations over Qm’s values, such
that (kmi,kmj) Rlm, if, according to
the expert judgement, kmi is not
less inherent in (typical to) Cl than
kmj; m=1,…,M; l = 1, …,L.
Relations of Dominance by Inherence in a correspondent class


Rl  ai , a j  ai , a j  A, m  1, M aim , a jm  Rml , l  1, L
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Rules in NORCLASS
1. If the expert assigns an object ai to the class Cl,
any object aj, such that (aj, ai)  Rl , belongs to
Cl as well.
2. If, according to the expert judgement, an object
ai, does not belong the class Cl, any object aj,
such that (ai, aj)  Rl, does not belong to Cl as
well.
Violation of the rules above means the expert’s error
and has to be corrected once it has been revealed.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
NORCLASS Rules’ Effects
a1
C1
a2
a3
1,1,1,3
a6
1,1,2,3
1,1,1,2
1,1,2,2
a10
1,2,1,2
a11
1,2,1,3
a12
1,1,2,1
a8
a5
a9
a4
a16
a14
2,1,1,2
2,1,1,3
2,1,2,3
a24
2,1,1,1
a17
a18
1,2,2,3
a7 1,2,1,1
1,2,2,1
a15
1,2,2,2
C2
1,1,1,1
a21
2,1,2,1
a20
2,1,2,2
2,2,1,3
2,2,1,2
a23
2,2,2,2
a23
a20
a24
a13
a19
2,2,1,1
a22
2,2,2,1
a22
1,1,1,3
1,1,1,2
a21
a13
1,1,2,1
1,2,1,2
1,2,2,3
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
2,1,1,3
a5
a8
2,1,1,2
2,1,2,1
a9
a10
a6
2,1,2,2
2,1,2,3
2,2,2,3
2,2,1,1
a2
2,2,1,2
a4
a1
2,2,2,3
2,1,1,1
a12
1,2,2,1
1,2,2,2
a7
1,2,1,1
a14
a15
1,2,1,3
a11
a17
a18
1,1,2,2
a19 a
16
1,1,2,3
1,1,1,1
a3
2,2,1,3
2,2,2,2
2,2,2,1
Advantages and Disadvantages
of NORCLASS
Advantages
Disadvantages
1. NORCLASS is based on so
1.
called Inherence Hypothesis
(IH): an expert is able to order
the values of any attribute
independently of the values of
other attributes. IH-based rules
2.
allow to reduce significantly
(up to 65% in average) a number
of objects presented to an expert
directly.
2. NORCLASS allows to construct
the complete (up to the expert
knowledge) and consistent set
of classification rules.
3.
NORCLASS doesn’t provide for
any aids for problem structuring.
Classes, attributes, values and
binary relations are revealed
informally.
Non-flexible dialogue with an
expert: he/she is presented Mattribute objects as whole, while the
expert may need a part of such
information only.
It is impossible to add a new
class, attribute or value in the
course of classification.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Modifications for NORCLASS
Effectiveness Improvement
1. Restatement a problem to include the formal phase of its
structuring*.
2. Changing the dialogue strategy in order to:
• make it more flexible and, thus, less cognitively onerous
for en expert;
• reduce further a number of questions to be asked to an
expert in a view of his/her classification rules eliciting;
• provide for additional possibilities for rules’ consistency
control.
----------------------*Eugenia M. Furems. Domain Structuring For Knowledge-Based Multiattribute Classification (A Verbal
Decision Analysis Approach) (2010) TOP, Springer Berlin / Heidelberg, DOI 10.1007/s11750-0090133-0
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Reformulation a problem
Multiattribute classification problem is stated as two interrelated
sub-problems:
It is given:
Some Application Domain each object of which may belong to
one or more classes
It is required:
1.
2.
To define the Structure of the Application Domain, i.e.,
l
m
m
m
To assign each aiA (A=K1 x K2 x … x KM) to a class/classes from
C on the basis of the expert’s knowledge so that the resulting
classification is both complete (up to the expert’s knowledge) and
consistent.
S  (C, Q,K 
,V
R
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
)
Explicit Structuring
(Pre-defined Classes C1, C2, C3)
ATTRIBUTES
apart form C1
Values of Q1 for C1
Q1
k11
Q2
Other classes k11 is
admissible for
C2
C3
Other classes k12 is
admissible for
k12
C3
apart from C1
Other values of Q1 for C3
apart from k11,k1,3
k14
Other values of Q1 for C2
k13
Other classes k13 is
admissible for
C3
apart
from k11
Other classes k14 is
admissible for
C1
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
C4
apart from C3
Structuring by Examples
Example for C1
A is a value
of Q1 (k11=A)
If <A> & <B>, then C1
B is a value
of Q2 (k21=B)
Example for C2
C2
C3
Other values
for C2
If <D> & <E>, then C2
D is a value of Q2
(k22=D)
Other classes
k11 is admissible for
k13
E is a value of Q3
(k31=E)
Other classes k31
is admissible for
C1
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
C3
Classification Rules Elicitation
ai=(x1,x2,x3,x4), xmKm
System:
Expert
System
Expert
System
x2
Q3 ?
x2x3
Q4 ?
x2x3x4
Expert: C1
Rule: If ‘any value’ of Q1, and x2 upon Q2, and x3 upon Q3 ,
and x4 upon Q4, than C1
Extension the Rule according to Dominance Inherence:
If ‘any value’ of Q1, and any k2i, such that (k2i, x2) R12, and any k3j,
such that (k3j,x3)  R13, and any k4s, such that (k4s, x4) R14, than C1
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Effect of Dialogue Strategy Modification
(Class C1)
a1
Before
a2
a3
1,1,1,3
a6
1,1,2,3
1,1,1,2
1,1,2,2
a10
1,2,1,2
a11
1,2,1,3
a12
1,1,2,1
a8
a5
a9
a4
a16
a14
2,1,1,2
2,1,1,3
2,1,2,3
a24
2,1,1,1
a17
a18
1,2,2,3
a7 1,2,1,1
1,2,2,1
a15
1,2,2,2
After
1,1,1,1
a21
2,1,2,1
a20
2,1,2,2
2,2,1,3
2,2,1,2
a23
2,2,2,2
a19
2,2,1,1
a22
2,2,2,1
a3
1,1,1,3
a6 a
9
a12
1,1,2,1
a8
1,1,2,2
1,2,2,3
1,2,1,2
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
1,2,2,1
a18
a19
a16
2,1,1,2
2,1,2,1
a17
2,1,1,3
1,2,2,2
2,1,1,1
a14
a15
a20
2,1,2,2
2,1,2,3
2,,2,3,3
2,2,1,3
2,2,1,1
a22
2,2,1,2
a21
a24
2,2,3,3
1,2,1,1
a10
a11
1,2,1,3
a13
a7
1,1,1,2
a5
1,1,2,3
1,1,1,1
a4
a2
a13
a1
a23
2,2,2,2
2,2,2,1
Effect of Dialogue Strategy Modification
(Class C2)
a23
Before
a24
a22
1,1,1,3
a19
1,1,2,3
1,1,1,2
1,1,2,2
1,1,2,1
a10
1,2,2,2
2,1,1,2
2,1,1,3
a4
2,1,2,1
2,2,1,3
a3
2,2,1,1
a2
a6
2,1,2,2
a11
2,2,1,2
2,2,2,2
2,2,2,1
a22
1,1,1,3
1,1,1,2
a21
a13
1,1,1,1
1,1,2,1
1,2,1,2
1,2,2,3
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
2,1,1,3
a5
a8
2,1,1,2
2,1,2,1
a9
a10
a6
2,1,2,2
2,1,2,3
2,,2,3,3
2,2,1,1
a2
2,2,1,2
a4
a1
2,,2,3,3
2,1,1,1
a12
1,2,2,1
1,2,2,2
a7
1,2,1,1
a14
a15
1,2,1,3
a11
a17
a18
1,1,2,2
a19 a
16
1,1,2,3
a23
a20
a24
a5
a8
a9
2,1,2,3
a1
2,1,1,1
a12
1,2,2,1
a7
1,2,2,3
1,2,1,1
a14
1,2,1,2
a15
1,2,1,3
a13
a17
a18
a21
a16
a20
After
1,1,1,1
a3
2,2,1,3
2,2,2,2
2,2,2,1
AD Structure Adjustment
• Expert has opportunity to specify a new class
He/she is asked to determine admissibility of all values of the attributes from
the current set Q to such class before to proceed to the next object classification.
• Expert has opportunity to inquire about a new attribute
He/she names it, lists all of its possible values and specifies their correspondent
admissibility to the classes. The first value of the new attribute is added to
the description of the object under consideration, and it is presented to the
expert in addition to information she/he knows already for such object
• Expert points out incompatible values in the object’s
description
All objects with such incompatible values’ combinations are excluded
from the set A.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Additional Consistency Control
Possible contradictions:
1. The expert specifies a rule for a class
with the value(s) in left-hand part, he/she
determined as inadmissible to the class
at the stage of structuring
2. The rule elicited last is inconsistent with
the rules elicited previously.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Explicit Rules Inconsistency
Rule 1
If any value of Q1,
and x2 upon Q2, and
x3 upon Q3 ,
and x4 upon Q4 , then C1
If x1 upon Q1,
and x2 upon Q2, and
x3 upon Q3 ,
and x4 upon Q4 , then C1
Contradiction
Rule 2
If x1 upon Q1, and x2
upon Q2 , and any value
of Q3, and x4 upon Q4 ,
then C2
If x1 upon Q1, and x2
upon Q2 , and
x3 upon Q3 ,
and x4 upon Q4 , then C2
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Conclusions
1.
2.
3.
VDA-based techniques for multiattribute classification use
only those operations of eliciting information from a
DM/expert and such information processing so that both
intermediate and resulting conclusions are traceable (wellexplainable) to the expert.
Proposed modification of a dialogue strategy for
NORCLASS allows to make an expert’ knowledge
acquisition more close to his/her routine practice, and, thus,
to facilitate for him/her the rules’ eliciting procedure.
In addition, proposed modification allows to eliminate
disadvantages of NORCLASS (absence of preliminary
structuring procedures, non-flexible dialogue, impossibility
of new classes, attributes and their values specification,
etc.) and to reduce further the number of objects to be
presented the expert directly for his/her classification rules
eliciting.
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011
Thank You!
MCDM 2011, Jyvaskyla, Finland,
June 13-17, 2011