Download The SAS neural network application

The SAS Neural
Network Application
DtaPaper Title
Gerhard Held
SAS Institute
European Product Manager
Analysis Applications
The SAS Neural Network
Application (NNA)
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Data Mining and Neural Networks
The SAS Neural Network Application
(NNA)
Demonstration
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Data Mining and Neural Networks
The current Situation:
“Computers promised us a Fountain of Wisdom,
but delivered us a Flood of Data”
Gregory Piatetsky-Shapiro, 1991
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Data Mining and Neural Networks
Data Warehousing Ideal for Data Mining
Operational
RDBMS
EIS
Data
Extractor
Transformation
Engine
OLAP
Risk
Metadata
Data Mining
Query and Reporting
Legacy
SAS
Information
Database
Internet Exploitation
Metadata Manager
Intelligent
Client/Server
External
Organisation
Product
Data Visualisation
OO RAD
Management
Customer
DSS
Loader
Scheduler
Quality
Exploitation
Market
Future
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Data Mining as a Process
Business / IT Environment
DBMS
Data
Warehouse
Data Mining
Internal
Processing
Business
Reporting
and Graphics
Informed
Business
Decisions
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Sample
Visual
Exploration
Variable
grouping,
subsetting
Neural
Networks
Tree-based
Models
Assess
Sampling ?
Explore
Manipulate
Model
Data Update ?
New Questions ?
Sample
Clustering,
Factor,
Correspond.
Adding or
subsetting
of Records
Statistical
Techniques
Assess
Time Series
Analysis
Data Mining and Neural Networks
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NNA is embedded in Data Mining
Offering
So what is the NNA specifically?
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The SAS Neural Network
Application (NNA)
The NNA initial Prod is:
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The Power of Neural Networks in an
easy-to-use Application
Enterprise oriented:
 Data Diversity
 Consistent Implementation
 Distributed C/S, Data and Compute S.
Comes with 2-day Ambassador Training
Some Information Sources for Neural
Networks included
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The SAS NNA
Integrates:
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Data Access / Data Specification
Model Definition, Training Options, Training
Reporting (Weights, Badness of Fit,
Networks, Predictions…)
Save / load of trained Networks
Interfaces to the SAS System (SAS/ASSIST,
SAS/INSIGHT etc.)
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The SAS NNA
Differences to SAS NNA beta:
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Re-engineered Interface
Much more Flexibility (latest TNN
Macros)
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The SAS NNA
Types of Models supported:
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Multilayer Perceptron
Radial Basis Functions (various)
Counter Propagation Networks
Learning vector Quantisation (LVQ)
Generalised Linear Models
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The SAS NNA
Training: Control / support of:
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Levels of Variables
Error Functions
Objective Functions
Combination Functions
Activation Functions
Link Functions
...
(Input / Target)
(to be minimised)
(Target)
(Hidden, Output)
(Hidden, Output)
(GLIM)
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The SAS NNA
Training: Control / support of (continued)
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Split of Training / Test Data
Max Iterations
Preliminary Runs
Selection of Training Technique (Algorithm)
Stopping: Convergence or Stopped Training
Mostly set automatically by NN Architecture
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The SAS NNA
Two “Modes”:
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End User Track (Defaults)
NN Specialist Track (Fine Tune)
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The SAS NNA
Availability NNA Initial Prod:
 UNIX (HP-UX, AIX, SUN)
July 96
 Win, OS/2
3Q96
 MF Compute Server
Orlando Server
Requirements:
 B, F, G, O
 INS
 E, I, ST, ASS
required
strongly recommended
recommended
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The SAS NNA
Demonstration
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Thank you for
your attention
DtaPaper Title
The SAS® System for successful decision making