Ensemble Based Quantification for 18O Labeled LC-MS

With the development of machine learning, researchers can get more accurate results for bioinformatics by using complex machine learning methods. However, these complex machine learning methods are always time consuming and computationally expensive. On the other hand, the methods like boosting in classification can be considered for those traditional “weak” methods to get better performance. By combining simple regression approaches, an ensemble based method is proposed in this paper for
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O labeled LC-MS. Experimental results show that this proposed method is capable for better quantification results.