NeuroXL Clusterizer

In finance, science, and business, analysts are often faced with the task of cluster analysis based on historical or measured data. Stock market analysts may wish to categorize a group of stocks as buy, sell, or hold; a cancer researcher may wish to categorize a list of tumors as benign or malignant; a mortgage analyst may wish to categorize loans as good or bad. A major difficulty faced by such analysts is that the data to be categorized can often be quite complex, with numerous interrelated variables. The time and effort required to develop a model to solve accurately such clusterization problems can be significant.

Neural networks are a proven, widely used technology to solve such 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 Clusterizer software by AnalyzerXL implements self-organizing neural networks, which perform categorization by learning the trends and relationships within your data.

Despite their effectiveness, neural networks are often not used for cluster analysis due to their complexity. NeuroXL Clusterizer removes these barriers by hiding the complexity of its advanced neural network-based methods while taking advantage of analysts' existing knowledge of Microsoft Excel spreadsheets. You simply supply the data, and NeuroXL Clusterizer implements a neural network that segments your data according to your preferences. Since users supply data through the familiar Excel interface, learning time is minimal, greatly reducing the interval between installing the software and performing cluster analysis. The application is extremely intuitive and easy-to-use for beginners, not requiring any previous knowledge of neural networks, yet powerful enough for the most demanding professionals.