Neural Connection s four powerful neural networks give you better performing models
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1 Neural Connection 2.1 Neural Connection s four powerful neural networks give you better performing models Build better models for more effective classification, prediction, time series forecasting and clustering
2 Build better performing mod Apply Neural Connection to your toughest modeling problems and find hidden patterns and trends in your data. Its powerful combination of neural networks and traditional statistical methods is an intelligent way to get the most value from your data. Neural Connection is a powerful neural network modeling software package that helps users to build better models faster. Scientific Computing and Automation December 1998 Neural Connection can outperform traditional statistics alone by using neural networks to learn patterns in your data set and model data more accurately. With Neural Connection, you ll build better performing models for classification, prediction, time series forecasting and clustering. Neural Connection s intuitive interface illustrates the steps in your analytical process, from data access through analysis to presentation, so you build models swiftly. Get a return on your data investment The data you acquire can either lead to opportunities or remain unused in your data stores. Neural Connection enables you to build powerful models that help you discover critical elements in your data that you wouldn t find using less sophisticated techniques. Used proactively, Neural Connection can be a cornerstone in your data mining efforts, empowering you to leverage and explore all of your data. Use neural networks to identify opportunities What makes neural networks so unique and so powerful is their ability to model complex patterns and trends automatically. Neural networks are made up of layers of nodes that find features in your data. You don t have to be a statistician or programmer to find patterns and trends because Neural Connection s powerful neural networks identify these features by training or iteratively learning patterns. And, after training and assessing the neural network, you can easily deploy the model on new data sets. Use Neural Connection for: Classification (also known as statistical pattern recognition) predict group membership based on input variables. Prediction predict a continuous outcome, such as real estate pricing models, using one or more predictors. Prediction is similar to linear regression, but with no assumption of linear model form. Time series forecasting use past time periods to predict the current observation and produce n-step-ahead forecasts. Clustering produce a Self-Organizing Map a spatial depiction of a set of data records that often suggests clusters or meaningful groupings of the objects. Marketing research Examine customer profiles Forecast sales Uncover consumer preferences Database marketing Optimize mailing lists Profile customer groups Segment markets Financial analysis Manage stock funds Perform credit risk analysis Detect fraud Statistical research Perform data modeling Profile populations and subgroups Determine data segments Operational analysis Run logistics analysis Manage cash flow Organize transportation planning Health care Forecast treatment costs Perform medical outcomes analysis Predict hospital length-of-stay
3 els to identify opportunities The Multi-Layer Perceptron dialog box gives you control over MLP settings and enables you to tailor your analysis. Meet all your neural computing needs Get all the neural computing tools you need in one package from preparing your data to tweaking the results. Choose from four neural network tools and three statistical tools for modeling and forecasting. The neural network tools cover prediction and classification with any data pattern even nonlinear. The neural network tools include: Multi-Layer Perceptron, Radial Basis Function, Bayesian Neural Network and the Kohonen Network. If 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 techniques. Build better performing models with powerful tools without programming Neural Connection gives you the flexibility to completely control your analysis. You build your models using intuitive, icon-based tools. Quickly select tools from the tool palette to build your model step-by-step. Each tool is easily moved and connected with your mouse, so you set up your analysis quickly. All of the tools have intelligent defaults so beginners get started quickly and more experienced users can change parameters, such as specifying the transfer function, starting weights or number of hidden neural network layers. You ll also save time with Neural Connection s data management features. From viewing descriptive statistics to performing transformations, you get the tools you need to prepare your data for analysis. It s easy to begin analysis. Simply click your mouse to start data moving through your network to build the model. The logic of your analysis is graphically presented and easy to understand no more programming. Explore your models in depth After your model is built and your data analyzed, Neural Connection gives you many 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. For even 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. Simply apply a trained model to new data and get results quickly. You can document your model by incorporating the final network parameters and weight values into your reports or publications. See the results as two side-by-side sensitivity graphs: a contour plot and a cross-section. With the What-If? tool, you can reposition two variables in the analysis to see how the change affects your outcome. Time series and 3-D graphs let you quickly visualize your model s results. Spot trends in your data by using the time series plots to display predictions and actual values over time. Analyzing your results with dynamic 3-D graphs enables you to see the peaks and valleys of your data that you might miss with simpler models. Experiment with your models for tailored analysis Neural Connection makes it easy for you to experiment with your models by adjusting the neural network parameters. You can change parameters such as transfer functions, starting weights or the number of hidden neural network layers or nodes. You can even create specialized models for your specific needs by combining the modeling and forecasting tools. For example, create committees of models for a combined prediction. Neural Connection s Filter tool enables you to preprocess data before sending it to be trained by a neural network. To go even further with Neural Connection, there are two scripting languages that help you write production jobs or initialize models. The NetAgent scripting language also gives you the ability to write interactive applications complete with text instructions for others in your organization to use. Applications can be run by a novice user or as a batch job. The breakthrough features in Neural Connection are the perfect complement to your traditional statistical analysis. If you re involved in classification, prediction, time series analysis or clustering, Neural Connection is the data analysis answer for you.
4 Powerful tools for precise modeling Neural Connection offers an intuitive, visual environment that enables you to interact quickly with tools and models. This Neural Connection application shows the use of three neural networks in tandem (Lifestyle, Wealth, Response) to model direct mail responses as a function of background demographic and financial information. Input data Results Filtering tools Make better predictions by using Neural Connection's Input tool to allocate your date to Training, Validation and Test samples. This mechanism helps prevent overfitting (when a model s fit becomes too specific to the original data set) and gives you an estimate of your error in classification or prediction of new data. Modeling Prepare your data for analysis right in Neural Connection. Unlike other packages, which force you to prepare your data elsewhere, Neural Connection gives you the data preparation tools you need. The Filter tool gives you one-click access to descriptive statistics, transformations, quantiles and more. The histogram enables you to see your distributions. You can also easily select and deselect variables you want included in your analysis. What If? Visualize important peaks and valleys in your data. With 3-D contour plots in Neural Connection, you see the neural network s fitted model. View the trained neural network's predictions versus the known values of the response variable and the input values associated with the responses. Then, easily read the results of scoring a new data set in an already trained neural network. Output the scored data set as an system file. Graphs Customize your analysis with pull-down menus for each tool. Or, rely on the defaults already set for you. This Radial Basis Function dialog box shows many different ways to adjust and fine-tune your RBF analysis. Get the best look at your data interactions with the What If? tool. The What If? tool enables you to explore your model even further with a full-color contour plot, a cross-section plot and interpretive text comments. You can change the values of the input variables to explore their impact on the output variable.
5 Data mining with Neural Connection and complementary products Data mining function Application examples Neural Connection approach Complementary statistical and data mining approaches Classification Response modeling Credit scoring Fraud detection Churn analysis Cross-selling Neural networks Multi-layer Perceptron Radial basis function Bayesian neural network Discriminant analysis Logistic regression Polytomous logistic regression Neural networks Rule induction C5.0 AnswerTree Decision trees GOLDMineR Ordinal regression Clustering Market segmentation Kohonen network Hierarchical clustering K-means clustering Kohonen network K-means Prediction/ Modeling Ranking, scoring customers Pricing models Neural networks Multi-layer Perceptron Radial basis function Bayesian neural network Linear Regression Nonlinear regression Neural networks AnswerTree Regression trees (C&RT) GOLDMineR Ordinal regression Time series forecasting Sales forecasting Interest rate prediction Inventory forecasting Neural networks Multi-layer Perceptron Radial basis function Bayesian neural network ARIMA models Exponential smoothing Time series regression Neural networks When used in conjunction, Neural Connection 2.1 and the product line make an unbeatable data analysis and data mining package. Neural Connection's powerful neural networks can produce models that outperform conventional methods for classification, clustering, prediction and time series forecasting. The product line offers a variety of traditional statistical techniques that complement Neural Connection and enable you to discover the power of data mining.
6 Specifications DATA MANAGEMENT TOOLS Data Input tool Data input file formats: comma-delimited, field-counted, record-delimited, fixed-format ASCII, system file, SYSTAT system file, Excel worksheet Handles missing data No limit on number of cases in the run data set 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 Transformations: square, cube, square root, reciprocal, linear, selection on inequality range, exponential, natural logarithm, common logarithm, logarithm of ratio, 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 TOOLS Multi-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 Principal Component Analysis OUTPUT TOOLS Data output Save results in 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 Save results in system file or text file View prediction or classification values for training, validation, or test data View classification results and error measures Graphics output 3-D wire-mesh plot shows network predicted output versus two inputs 3-D rotation What If? 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 Neural Connection 2.1 is a stand-alone product. However, when you have installed on your machine and then install Neural Connection, Neural Connection is added to s Analysis menu. You can manipulate data in, and then start Neural Connection, which automatically passes 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 RAM memory minimum 4MB free hard drive space Neural Connection is Y2K enabled. For information on other products see the Y2K information page at Learn more about Contact your nearest office or visit us at Inc Toll-free Argentina Asia Pacific Australasia Toll-free Belgium Benelux Brasil Czech Republic Danmark Federal Systems (U.S.) Toll-free Finland France Germany Hellas Hispanoportuguesa Hong Kong India Ireland Israel Italia Japan Kenya Korea Latin America Malaysia Mexico Norway Polska Russia Scandinavia Schweiz Singapore South Africa Taiwan UK In addition to these offices, has a worldwide network of distributors. Contact the office nearest you for assistance. is a registered trademark and the other products named are trademarks of Inc. All other names are trademarks of their respective owners. Printed in the U.S.A Copyright 1999 Inc. NC21BRO-0499W
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