An efficient data pre-processing model for machine learning

Abstract

Currently, data pre-processing is one of the areas of nice interest as a result of it permits the discovery of hidden and infrequently attention-grabbing patterns in massive volumes of information. information scientists pay most of their time on information preparation tasks that have investigation regarding the info, loading information, and cleanup information, in line with an exploration conducted by Anaconda. The real-world massive information sets square measure obtained from several sources and contain data that tend to be incomplete, creaky, and inconsistent thence required correct investigation. during this context, it’s vital to arrange information to satisfy the necessities of information mining algorithms. this can be the role of the information pre-processing stage, within which information cleanup, transformation, and integration, or information spatiality reduction square measure performed. just about any sort of information analytics, information science or AI development needs some sort of information pre-processing to supply reliable, precise, and strong results for enterprise applications.

Cite this paper

@article{lawatre2021efficient,
  title = {{An efficient data pre-processing model for machine learning}},
  author = {Lawatre, Piyush and Muzzammil, Mohammed and Hingal, Rishabh and Khan, Fatir and Khan, Rizwan},
  journal = {International journal of advance research, ideas and innovations in technology},
  volume = {7},
  number = {3},
  year = {2021}
}

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