AI Article Synopsis
- Neural networks are intelligent learning systems that identify relationships among real-world object descriptors.
- They are used as computational algorithms for optimization tasks like parameter estimation, model selection, and improving generalization.
- In bioinformatics, supervised neural networks are crucial for tasks such as classification, function approximation, knowledge discovery, and data visualization.
Article Abstract
Neural networks are a class of intelligent learning machines establishing the relationships between descriptors of real-world objects. As optimisation tools they are also a class of computational algorithms implemented using statistical/numerical techniques for parameter estimate, model selection, and generalisation enhancement. In bioinformatics applications, neural networks have played an important role for classification, function approximation, knowledge discovery, and data visualisation. This chapter will focus on supervised neural networks and discuss their applications to bioinformatics.
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| http://dx.doi.org/10.1007/978-1-60327-241-4_12 | DOI Listing |
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