Solving Data Mining Problems Through Pattern Recognition

Apply pattern recognition to find the hidden gems in your data!

Data mining technology is helping businesses everywhere to work smarter by revealing unknown patterns within existing archives. Applying the latest advances in pattern recognition software can give you a key competitive edge across all data mining applications. The tutorials and software package included in Solving Data Mining Problems through Pattern Recognition take advantage of machine learning techniques and neural networks to help you get the most out of your data. Besides explaining the most current theories, Solving Data Mining Problems through Pattern Recognition takes a practical approach to overall project development concerns.

The rigorous, multi-step method includes:

• Defining the pattern recognition problem
• Collection, preparation, and preprocessing of data
• Choosing the appropriate algorithm and tuning algorithm parameters Training, testing, and troubleshooting.

Pattern classification, estimation, and modeling are addressed using the following algorithms:

• Linear and logistic regression
• Unimodal Gaussian and Gaussian mixture
• Multilayered perceptron/backpropagation and radial basis function neural networks
• K nearest neighbors and nearest cluster
• K means clustering.

While some aspects of pattern recognition involve advanced mathematical principles, most successful projects rely on a strong element of human experience and intuition. Solving Data Mining Problems through Pattern Recognition provides a strong theoretical grounding for beginners, yet it also contains detailed models and insights into real-world problem-solving that will inspire more experienced users, be they database designers, modelers, or project leaders.

This book includes a free, 90-day trial copy of Pattern Recognition Workbench, a powerful, easy-to-use system that combines machine learning, neural networks, and statistical algorithms to help you apply pattern recognition to your data right now. The enclosed CD-ROM runs under Windows(r) 95 and Windows NT(tm).