Data visualization and data mining of continuous numerical and discrete nominal‐valued microarray databases for bioinformatics

Purpose – To present research in the area of the applications of modern heuristics and data mining techniques in knowledge discovery.Design/methodology/approach – Applications of data mining for neural networks using NeuralWare Predict® software, genetic algorithms using Biodiscovery GeneSight® (2005) software, and regression and discriminant analysis using SPSS® were selected for bioscience data sets of continuous numerical‐valued Abalone fish data and discrete nominal‐valued mushroom data.Findings – This paper illustrates the useful information that can be obtained using data mining for evolutionary algorithms specifically as those for neural networks, genetic algorithms, regression analysis, and discriminant analysis.Research limitations/implications – The use of NeuralWare Predict® was a very effective method of implementing training rules for neural networks to identify the important attributes of numerical and nominal valued data.Practical implications – The software and algorithms discussed in the ...

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