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The k nearest neighbor (kNN) rule is one of the most used techniques in data mining and pattern recognition due to its simplicity and low identification error.
The approach adopted draws on tools in the areas of data mining and pattern recognition including the techniques of Fisher correlation score and self-organising maps.
Through complex data mining and pattern recognition.
Machine learning, data mining, and pattern recognition algorithms are based on existing statistical inference models.
Clustering has been attracting a lot of research interests in data mining and pattern recognition community.
Analytical CRM frequently uses data mining and pattern recognition to accomplish this task -- it works well for companies in higher priced markets with a lot of competition.
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Cluster analysis is a widely used technique for grouping a set of objects into classes of "similar" objects and commonly used in many fields such as data mining, bioinformatics and pattern recognition.
Increasingly, computer vision, image analysis, data mining, machine learning and pattern recognition methods have been applied to microscopic images to extract biological information and to generate ontology databases.
This technique is widely used in data mining, machine learning and pattern recognition, and has also been applied to the field of bioinformatics [ 4].
Here, the authors use a combination of data mining, sequence analysis, and pattern recognition algorithms to predict a set of genes that credibly relate to a specific disease, X-Linked Mental Retardation. X-Linked Mental Retardation
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