Proceedings of the 2018 2nd International Conference on Computational Biology and Bioinformatics 2018
DOI: 10.1145/3290818.3290831
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Using Machine Learning Classifiers to Identify the Critical Proteins in Down Syndrome

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Cited by 5 publications
(8 citation statements)
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“…The first problem is multi class classification of all the data. Our results will be to compared with Kulan et al 24 and B.Feng et al 23 for this problem. They have reduced the dimension of the data from 77 proteins (excluding the categorical values) to 30 proteins.…”
Section: Feature Selectionmentioning
confidence: 80%
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“…The first problem is multi class classification of all the data. Our results will be to compared with Kulan et al 24 and B.Feng et al 23 for this problem. They have reduced the dimension of the data from 77 proteins (excluding the categorical values) to 30 proteins.…”
Section: Feature Selectionmentioning
confidence: 80%
“…As mentioned above, for this problem we are going to compare our results with Kulan et al [25] and B.Feng et al [24]. For classification technique 10-fold cross validation result.…”
Section: Multiclass Classification Problemmentioning
confidence: 94%
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