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In this paper we discuss the advancement and applications of Tree based classification and regression methods to semiconductor data. We begin the paper with a description of the problem, followed by an overview of the statistical-learning techniques we use in our case studies. We then describe how the challenges presented by semiconductor data were addressed with original extensions to tree-based...
We describe experiments with machine learning algorithms (ID3, C4.5, Bagged-C4.5, Boosted-C4.5 and Naive Bayes) and an algorithm made on the basis of a combination of genetic algorithms (GA) and ID3. To perform the experiments, the latter algorithm is implemented as an extension of the MLC++ library of Stanford University. The behaviour of the algorithm is tested using 24 databases including the databases...
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