Application and comparison of machine learning and database-based methods in taxonomic classification of high-throughput sequencing data

HIGHLIGHTS

• What: On this basis the aim of the study was to conduct a comparative ana­ lysis between these two methods while also investigating the merits of integrating multiple database-based methods. The authors have thoroughly compared the performance of different types of classifiers, aiming to highlight performance disparities between DB classifica­ tion algorithms and ML classifiers across diverse biological taxonomic levels. The model is trained by selecting features and splits iteratively and tested on separate data sets, including simulated ones, to evaluate performance. The primary reason for this is the necessity to load substantial reference databases into . . .
  

   

  

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