Build moreaccurate modelsUse neural networks to complement yourtraditional statisticalanalysis

Build your analysisgraphicallyThe icon-based work-space makes modelingquick and clear

Get more powerfulmodelingFour neural net toolsand 13 other data, modeling and outputtools give you more flexibility

Understand yourresults betterUse What If? and fourother output tools toexplore your model

The Neural Connection icon-based interface is designed to be easy to understand. Drag each toolinto place from the tool paletteon the right and simply createconnections between toolswith a mouse click. Use pop-up menus to change toolparameters. The graphical interface makes keeping track of the logic behind your model easy. The graph on the right shows the magnitude

of the error as a function of the iteration.

Better models faster – deliver breakthroughtools for intelligent analysisWith Neural Connection™ from SPSS you can nowfind patterns in your data and build better modelsthan with traditional statistics.

Neural Connection gives you more power and flexibility for:■ Prediction■ Classification■ Time-series analysis■ Data segmentationNeural Connection improves productivity in market research, database marketing, financial research and scientific and statistical research.

Build more accurate data models with powerful toolsWith Neural Connection, you build your model using logical icon-based tools. Each tool is easily moved andconnected with your mouse, so setting up your analysis is fast. Then, click to start data moving through your network to build the model. The logic of your analysis is graphically presented and easy to understand.

Choose from four neural network tools and three statistical tools for modeling and forecasting. The neural network tools cover prediction and classificationwith any data pattern, even non-linear. The neural network tools are: Multi-Layer Perceptron, Radial Basis Function, Bayesian Neural Network and the Kohonen Network.

If you decide that you would like to enhance or benchmark your neural network analysis with traditional statistics, Neural Connection gives you: multiple regression, closest class mean classifier and principal component analysis tools.

Explore your models in depthAfter your model is built and your data analyzed, NeuralConnection gives you many output options to uncover answers from your data and present your results.

Neural Connection produces text output, file output,a time-series graph or a 3-D picture of your data. Foreven more in-depth information from your analysis, use the What If? tool. The unique What If? tool is an interactive, graphical way to explore your results and understand your models better. See your results as twoside-by-side sensitivity graphs: a contour plot and across-section. With these tools, you can reposition twovariables in the analysis to see how the change affectsyour outcome.

Neural Connection makes it easy for you to experiment with your models by adjusting the neuralnetwork parameters. You can change parameters such as transfer functions, starting weights or the number of hidden neural network layers or nodes.

To go even further with Neural Connection, there are two scripting languages that help you write produc-tion jobs or initialize models. The NetAgent scriptinglanguage also gives you the power to write interactiveapplications complete with text instructions for othersin your organization to use.

The breakthrough tools of Neural Connection are the perfect complement to your traditional statisticalanalysis. If you are involved in prediction, classification,time series analysis or data segmentation, Neural Connection is the data analysis answer for you.

Neural Connection 2.1

®

Neural Connection 2.1 specifications

Procedures

DATA MANAGEMENT TOOLSData Input tool■ Data input file formats: comma-delimited, field counted,

record-delimited, fixed format ASCII, SPSS system file, SYSTAT system file, Excel worksheet

■ Handles missing data■ No limit on number of cases in the run dataset■ Open development data: read data file on which you

will build and assess your neural network■ Open run data: read data file that will be scored by

an already trained neural network■ Designate field usage: input, target, reference, unused ■ Equalize classes■ Configure fields and generate simple summary statistics

Filter tool■ Summary statistics: number of cases, sum, mean,

variance, standard deviation, absolute deviation, skewness, kurtosis, range, interquartile range, quantiles

■ Histogram plot■ Tranformations: square, cube, square root, reciprocal,

linear, selection on inequality range, exponential, naturallogarithm, common logarithm, logarithm of quotient, arcsine square root, box-cox

■ Trimming■ Select variables for use in further analysis

Combiner tool■ Combine the output from two or more distinct network

objects into a single object■ Facilitates “committee” or “voting” models

Simulator tool■ Generates model output for any two input fields■ Model output “fills in” What If? graph and graphics

output graph

Time-series window■ Single-step or multi-step prediction■ Creates lagged inputs used in modeling■ Creates forecast variables

MODELING AND FORECASTING TOOLSMulti-Layer Perceptron tool■ Normalize input and output layer■ One or two hidden layers■ Optional automatic node generation■ Linear, sigmoidal or hyperbolic tangent transformation

of network output■ Random start values for network weights■ Set random seed for different trial starts■ Learning rule: conjugate gradient or steepest descent■ Weight updates for steepest descent: by pattern or

training epoch■ Stop training: stop button, maximum number of updates,

absolute size of root mean square error in training or validation sets, percent correct classification in training or validation sets

■ Use best network■ Up to 4,000 nodes per layer

Radial basis function tool■ Normalize input and output layers■ Error distance: euclidean or city block■ Function: spline, gaussian, multi-quadratic, inverse

multi-quadratic■ Specify number of centers at start■ Center positioning: sample points, random, or trial■ Network optimization: add extra centers up to a limit,

stop adding centers when there is no improvement■ Confidence outputs: put prediction error band

around predictions■ Use best network

Bayesian Neural Network tool■ Use validation set for training■ One or two hidden layers■ Optional automatic node generation■ Parameter groups: single weight group, weights grouped

by layer, separate weights and biases, automatic relevance detection

■ Train and use multiple models: most likely model or committee decision

Kohonen Network tool■ Dimensionality: 1 or 2■ Normalization: square or spherical■ Error response: euclidean distance or dot product■ Algorithm tuning parameters: learning rate, decay,

neighborhood size, neighborhood decay rate■ Output function: vector quantization, VQ codebook,

full response■ Kohonen network viewer■ Initial weight distribution: small random, random,

from data, small grid, grid■ Single or multiple models■ Optimization: double network size

Statistical tools■ Closest Class Mean Classifier■ Regression tool■ Principal Component Analysis tool

OUTPUT TOOLSData Output tool■ Save results in SPSS system file or text file■ Results include prediction or classification values

for training, validation, test, or run data■ Cross-tabulation matrix of classification results

Text Output tool■ Save results in SPSS system file or text file■ View prediction or classification values for training,

validation, or test data■ View classification results and error measures

Graphics Output tool■ 3-D wire-mesh plot shows network predicted output

versus two inputs■ 3-D rotation

What If? tool■ Contour plot plus vertical slice■ Interactive sensitivity plot

Time Series plot■ Display results of single-step or multi-step forecasts■ Shows actual and predicted values■ Shows Training-validation and run data sets

INTEGRATION WITH SPSSNeural Connection 2.1 is a stand alone product. However,when you have SPSS installed on your machine and then install Neural Connection, Neural Connection is added toSPSS’s analysis menu. You can manipulate data in SPSS, and then start Neural Connection, which will automaticallypass your active file to Neural Connection’s Input Tool.Neural Connection also reads SYSTAT files.

SYSTEM REQUIREMENTS

■ 486 or better PC■ Windows 95/98; Windows NT 4■ 16MB memory minimum■ 4MB free hard drive space

SPSS products

How to order

To place an order or to get more information, contact yournearest SPSS office or visit our World Wide Web site atwww.spss.com/.

SPSS Inc. United States +1.312.651.3000and Canada Toll-free: +1.800.543.2185SPSS Argentina +541.814.5030SPSS Asia Pacific +65.245.9110SPSS Australasia +61.2.9954.5660

Toll-free: +1800.024.836SPSS Belgium +32.162.389.82SPSS Benelux +31.183.636711SPSS Central and Eastern Europe +44.(0)1483.719200SPSS Czech Republic +420.2.24813839SPSS East Mediterranea and Africa +972.9.9526701SPSS Federal Systems (U.S.) +1.703.527.6777SPSS Finland +358.9.524.801SPSS France +33.1.5535.2700SPSS Germany +49.89.4890740SPSS Hellas +30.1.7251925SPSS Hispanoportuguesa +34.91.447.37.00 SPSS Hong Kong +852.2.811.9662SPSS Ireland +353.1.496.9007SPSS Israel +972.9.9526700 SPSS Italia +39.51.252573SPSS Japan +81.3.5466.5511SPSS Kenya +254.2.577.262SPSS Korea +82.2.3446.7651SPSS Latin America +1.312.651.3226SPSS Malaysia +603.704.5877SPSS Mexico +52.5.682.87.68SPSS Middle East and South Asia +91.80.545.0582SPSS Polska +48.12.6369680SPSS Russia +7.095.125.0069SPSS Scandinavia +46.8.506.105.50SPSS Schweiz +41.1.266.90.30SPSS Singapore +65.533.3190SPSS South Africa +27.11.706.7015SPSS Taiwan +886.2.25771100SPSS UK +44.1483.719200In addition to these offices, SPSS has a worldwide network of distributors.Contact the SPSS office nearest you for assistance.Printed in the U.S.A. NC21SPC-1298W

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