Classes of Model in Business Intelligence. Predictive, pattern recognition, risk analysis, optimization model.

1. OMega TechEd
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2. BUSINESS INTELLIGENCE
Classes Of Models
Mrs. Megha Sharma
M.Sc. Computer Science. B.Ed.

3. Classes Of Models
 Predictive Models.
 Optimization Models.
 Risk Analysis Models.
 Pattern recognition and
learning Models.

4. Predictive Models
 Predictive model is used to predict about unknown
future,by analysing past.
Predictive model improve decision making or to make
profitable decision learning from past experiences.
Applications: Fraud detection, Medical diagnosis,
credit scoring, predict sales and inventory.

5. Correlation Correlation is a statistical technique that can
show whether and how strongly pairs of
variables are related.
There are three possible results of a
correlational study: a positive correlation, a
negative correlation, and no correlation

7. Pattern Recognition And Learning Model
 A Pattern is an object process or event that can be given a name.
Pattern recognition is the study of how machine can observe the
environments and taking action according to what they observed.
It focuses on the recognition of patterns.
Examples: Recognizing a face, signatures and characters.

8. Pattern Recognition
System to classify three numbers 1,2,3
In all 3 numbers , we have some lines and curves.
1 2 3
Number No. Of Lines No. Of curves Pattern
1 3 0 (3,0)
2 1 1 (1,1)
3 0 2 (0,2)

9. Representation in 2D Space
3
2 3
2
1
1
0 1
2
3
No. of Lines
No. of curves

10. Risk Analysis Model
 “Risk analysis is the estimation of risk associated with the identified
hazards”.
Risk analysis methods used for determining the level of risk of our
business.
Risk analysis methods.
 Qualitative risk analysis
 Quantitative risk analysis.

11. Comparison
QUALITATIVE RISK ANALYSIS
Performs when numerical data are
inadequate or unavailable.
Compulsory.
Quick and Simple, No specific tools
required
E.g. Brainstorming, Questionnaire,
Judgement of specialist and experts.
Subjective evaluation of probability and
impact.
QUANTITATIVE RISK ANALYSIS
Enable us to assign values of occurrence
to the various risk identified, i.e. to
calculate the level of risk of the project.
Optional.
Take more time. Required specialized
tools
Detailed study.
Objective. Probabilistic estimation of time
and cost.
Low Medium High

12. Optimization Model
It is an art, process of methodology of making system design and decision as fully perfect,
functional or as effective as possible.
Optimization model arises naturally in decision making processes where set of limited
resources must be allocated in the most effective way to different entities.
Application:
 Banking Finance.
Logistics supply chain.
Network optimization.
Retail
Media and communication.

13. Thanks For Watching.
Next Topic : Data Mining.

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