NeuroXL Classifier is a neural network add-in for Microsoft Excel. NeuroXL Classifier (ClassifierXL) 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 Classifier uses only proven algorithms and techniques, and integrates seamlessly with Microsoft Excel. Neural networks are a proven, widely used technology to solve complex classification problems. Loosely modeled after the human brain, neural networks are interconnected networks of independent processors that, by changing their connections (known as training), learn the solution to a problem. NeuroXL Classifier software implements self-organizing neural networks, which perform categorization by learning the trends and relationships within your data. NeuroXL Classifier is a powerful, easy-to-use and affordable solution for advanced classification of simple and complex data. By harnessing the latest advances in artificial intelligence and neural network technology, it delivers accurate and fast classifications. Designed as an add-on to Microsoft Excel, it is easy to learn and use and requires no importing or exporting of data. 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 Classifier can be applied to solve problems in numerous industries and disciplines, including finance, business, medicine, and research science. NeuroXL Classifier's ability to handle numerous, often-interrelated variables makes it widely applicable to classifying market data. For example, a trader may wish to classify stocks as buy, hold, or sell being based on historical data.

Platform:Win95, Win98, WinME, WinNT 3.x, WinNT 4.x, WinXP, Windows2000, Windows2003, Windows Vista, Windows Vista Ultimate

System Requirements: There is no specific requirements