NeuroXL Package

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"NeuroXL is a neural network forecasting and data clustering add-in for Excel"
By SoftCns Editor: NeuroXL Package is a neural network add-in for Microsoft Excel. It consists of Predictor and Clusterizer.

NeuroXL Predictor
NeuroXL Predictor is a neural network forecasting tool that quickly and accurately solves forecasting and estimation problems in Microsoft Excel. It is designed from the ground-up to aid experts in solving real-world forecasting problems.

NeuroXL Predictor interface is easy-to-use and does not require advanced knowledge of neural networks, and is integrated seamlessly with Microsoft Excel. Five transmission functions are now available to choose: Threshold, Hyperbolic tangent, Zero-based log-sigmoid, Log-sigmoid and Bipolar sigmoid. Moreover, it is possible to save the trained network and then load it when necessary.

NeuroXL Predictor delivers accurate and fast predictions for your business, financial, or sports forecasting tasks. Designed as an add-on to Microsoft Excel, it is easy to learn and use yet powerful enough for the most demanding professionals.

NeuroXL Clusterizer
NeuroXL Clusterizer is an add-in for Excel designed to aid experts in real-world data mining and pattern recognition tasks. It hides the underlying complexity of neural network processes while providing graphs and statistics for the user to easily understand results. NeuroXL Clusterizer uses only proven algorithms and techniques.

NeuroXL Clusterizer is a solution for advanced cluster analysis of simple and complex data. By harnessing the latest advances in artificial intelligence and neural network technology, it delivers accurate and fast clustering. Designed as an add-on to Microsoft Excel, it is easy to learn and use and requires no importing or exporting of data.

NeuroXL Clusterizer can be applied to solve problems in numerous industries and disciplines, including finance, business, medicine, and research science. NeuroXL Clusterizer's ability to handle numerous, often-interrelated variables makes it widely applicable to cluster analysis of market data.