PASW Neural Networks
Find More Complex Relationships in Your Data
PASW Neural Networks offers non-linear data modeling procedures that enable you to discover more complex relationships in your data. Using these
procedures, you can develop more accurate and effective predictive models. The result? Deeper insight and better decision-making.
The procedures in PASW Neural Networks complement the more traditional statistics in PASW Statistics Base and its modules. Find new associations in
your data with PASW Neural Networks and then confirm their significance with traditional statistical techniques.
What is a Neural Network?
A computational neural network is a set of non-linear data modeling tools consisting of input and output layers plus one or two hidden layers. The
connections between neurons in each layer have associated weights, which are iteratively adjusted by the training algorithm to minimize error and provide accurate predictions.
How can you use PASW Neural Networks?
You can combine PASW Neural Networks with other statistical procedures to gain clearer insight in a number of areas:
- Market research
- Create customer profiles
- Discover customer preferences
- Database marketing
- Segment your customer base
- Optimize campaigns
- Financial analysis
- Analyze applicants' creditworthiness
- Detect possible fraud
- Operational analysis
- Manage cash flow
- Improve logistics planning
- Healthcare
- Forecast treatment costs
- Perform medical outcomes analysis
In an MLP procedure like the one shown here, nodes in the input and output layers are connected to nodes in one or more hidden layers.
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