Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. The wide acceptance can be attributed to its robustness to high dimensionality problem. However, when the high-dimensional data is a sparse one, RF procedures are ineffi...

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書目詳細資料
主要作者:	Oyebayo, Olaniran Ridwan
格式:	Thesis
語言:	English English English
出版:	2018
主題:	QA76.75-76.765 Computer software
在線閱讀:	http://eprints.uthm.edu.my/326/1/24p%20OLANIRAN%20RIDWAN%20OYEBAYO.pdf http://eprints.uthm.edu.my/326/2/OLANIRAN%20RIDWAN%20OYEBAYO%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/326/3/OLANIRAN%20RIDWAN%20OYEBAYO%20WATERMARK.pdf
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